Detailed Action
1. Claims 1-20 are pending.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Drawings
3. The drawings filed on 06/01/2022 are accepted.
Oath/Declaration
4. For the record, the Examiner acknowledges that the Oath/Declaration submitted on 06/01/2022 has been received.
Information Disclosure Statement
5. The information disclosure statements (IDS) submitted on 6/1/2022, 10/12/2023 and 4/25/2024 have been considered. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, an initialed and dated copy of Applicant's IDS form SB08 filed 6/1/2022, 10/12/2023 and 4/25/2024 are attached to the instant Office action.
Specification
6. Examiner objects the Specification of current Application para [0024] because of typographical error. Applicant stated at para [0024] 2nd line: “a mathematical model of the blood vessel, by busing two layers of the single-layer mesh model …”. Examiner assumes a typo has been occurred above bolded and underlined word “busing”, therefore an appropriate correction is required in this scenario (e.g., by using two layers of the single-layer mesh model).
Claim Objections
Claims 2 and 14 is objected to because of the following informalities:
The 2nd limitation in claim 2 recites “sequentially combining and converting every N triangles into a N-gon …”. Examiner assumes a grammatical mistake happened in this scenario, instead of “triangles”, the claim language should be corrected as “every N triangle”.
The 1st limitation in claim 14 recites “performing image processing for the blood vessel partial area image to acquire an rough trend line of the blood vessel …;”. It is assumed a grammatical mistake/typo happened in this scenario. Appropriate correction is required (e.g., performing image processing for the blood vessel partial area image to acquire a rough trend line of the blood vessel …).
Examiner Notes
8. Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. The entire reference is considered to provide disclosure relating to the claimed invention. The claims & only the claims form the metes & bounds of the invention. Office personnel are to give the claims their broadest reasonable interpretation in light of the supporting disclosure. Unclaimed limitations appearing in the specification are not read into the claim. Prior art was referenced using terminology familiar to one of ordinary skill in the art. Such an approach is broad in concept and can be either explicit or implicit in meaning. Examiner's Notes are provided with the cited references to assist the applicant to better understand how the examiner interprets the applied prior art. Such comments are entirely consistent with the intent & spirit of compact prosecution.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
9. Claims 18 and 19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim 18 recite the limitation: “A device for synthesizing a mathematical model of a blood vessel, used for the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 1, comprising: a three-dimensional blood vessel model structure, a single-layer mesh model structure and a blood vessel mathematical model structure connected in sequence; the blood vessel mathematical model structure being connected with the three-dimensional blood vessel model structure;” The three elements above “three-dimensional blood vessel model structure, a single-layer mesh model structure and a blood vessel mathematical model structure” are non-physical mathematical entities. Further, “performing N-gon meshing” seems to indicate the single-layer mesh model is itself, which is not physical.
Claim limitations of claim 18 is found to be indefinite under 35 U.S.C. 112(b) for failure to disclose sufficient corresponding structure, e.g., a device for synthesizing a mathematical model of a blood vessel, comprising: three-dimensional blood vessel model structure, a single-layer mesh model structure and a blood vessel mathematical model structure” in the specification that performs the entire claimed function. It is unclear whether the supporting structure or the algorithm is adequate to perform the entire claimed function. However, if there is no corresponding structure disclosed in the specification i.e., the limitation is only supported by software or computer program (as per Specification of current Application para [0080 and 00191]) and does not correspond to an algorithm and the computer or microprocessor programmed with the algorithm), then the limitation should be deemed indefinite as discussed above, and the claim should be rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. (See MPEP 2181(II)(B)).
Dependent claim 19 does not resolve the indefinite issue in the base claim 18, and thus is also rejected under 112(b) by virtue of their dependence on the rejected base claim.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
10. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite a mathematical calculation; MPEP 2106.04(a)(2)(I).
Step 1
The claims under Step 1 are directed towards a method (claims 1-17), apparatus or device (claims 18-19) and computer storage medium (article of manufacture, claim 20).
Claim 1 recites:
A method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis, comprising: (field of use) (See Step 2A Prong 2 and Step 2B)
performing three-dimensional modeling according to a real-time diameter Dt of a blood vessel, a length L of a blood vessel centerline and a stenotic section to form a three-dimensional model of the blood vessel having a stenotic lesion section; (Mathematical Concepts)
performing N-gon meshing along a circumferential surface of the three-dimensional model of the blood vessel having the stenotic lesion section to form a single-layer mesh model where N ≥ 6; (Mathematical Concepts)
performing surface layering on the single-layer mesh model to form a double-layer mesh model, that is, the mathematical model of the blood vessel. (Mathematical Concepts)
Step 2A, prong 1:
The limitations of claim 1: “performing three-dimensional modeling according to a real-time diameter Dt of a blood vessel, a length L of a blood vessel centerline and a stenotic section to form a three-dimensional model of the blood vessel having a stenotic lesion section; performing N-gon meshing along a circumferential surface of the three-dimensional model of the blood vessel having the stenotic lesion section to form a single-layer mesh model where N ≥ 6; performing surface layering on the single-layer mesh model to form a double-layer mesh model, that is, the mathematical model of the blood vessel.” are recitations of Mathematical Concepts. According to conventional meaning in the art, the “3D mesh model” is based on math or using math. The claim language "the mathematical model" redefines the ordinary interpretation somewhat to force a mathematical interpretation. Accordingly, at step 2A, prong one, claim 1 as a whole is found to recite a judicial exception and is drawn to an abstract idea.
Step 2A, Prong 2:
This judicial exception is not integrated into a practical application because the claim language only recites elements that can practically be performed using math or based on math. Therefore, the claim 1 recites an abstract idea because it does not impose any meaningful limitations on practicing the abstract idea. Claim 1 has no additional limitations that integrate the abstract idea into a practical application. The preamble: “A method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis,” is recitation of field of use, i.e., this amount to merely indicating a field of use or technological environment and cannot integrate a judicial exception into a practical application.
Step 2B:
The claim 1 as a whole does not include any further additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with in the Step 2A, Prong Two analysis, with respect to integration of the abstract idea into a practical application. The additional element: A method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis,” is recitation of field of use, this amount to merely indicating a field of use or technological environment and does not amount to significantly more than the judicial exception.
Therefore, the claim 1 is not patent eligible under 35 USC 101.
Claims 2-20 are rejected as a Judicial Exception (JE) since they do not add significantly more than the abstract idea or a practical application.
Claims 2 and 3 are dependent on independent claim 1 and includes all the limitations of claim 1. The limitations of claims 2 and 3 are recitations of Mathematical Concepts. According to conventional meaning in the art, the “3D mesh model” is based on math or using math. The claim language "the mathematical model" redefines the ordinary interpretation somewhat to force a mathematical interpretation. Therefore, the limitations of claims 2 and 3 do not amount to significantly more than the abstract idea.
Claims 4 and 5 are dependent on independent claim 1 and includes all the limitations of claim 1. The limitation of claim 4: “the triangle that uses as the smallest unit is an isosceles triangle” is recitation of non-functional data description which does not add anything more to overcome the abstract idea. The 1st limitation of claim 5: “acquiring a blood vessel wall thickness …” is recitation of Mere data gathering, (See MPEP 2106.04(d) referencing MPEP 2106.05(g), example (iv): Obtaining information about transactions). The 2nd to 4th limitations of claim 5 are recitations of Mathematical Concepts, because performing mesh model and forming double-layer mesh model, are based on math or using math. Therefore, the limitations of claims 4 and 5 do not amount to significantly more than the abstract idea.
Claims 6 and 7 are dependent on independent claim 1 and includes all the limitations of claim 1. The limitations of claim 6: “acquiring two-dimensional coronary artery angiogram images …; obtaining a real-time diameter of the blood vessel and the length of a straightened blood vessel centerline …; acquiring the stenotic section of the coronary artery, to obtain a three-dimensional model of the blood vessel having a stenotic lesion section” are recitations of Mere data gathering (See MPEP 2106.04(d) referencing MPEP 2106.05(g), example (iv): Obtaining information about transactions). Further, the limitation of claim 6: “performing three-dimensional modeling …” is recitation of Mathematical Concepts, because performing 3D mesh model is based on math or using math. The last limitation of claim 6: “projecting the stenotic section onto the truncated cone three-dimensional model” is recitation of Mental Processes using evaluation or judgement. The limitations of claim 7: “extracting a blood vessel centerline …; obtaining an image of a straightened blood vessel …; obtaining a straightened blood vessel contour line …; acquiring geometric information of the straightened blood vessel,” are recitations of Mere data gathering (See MPEP 2106.04(d) referencing MPEP 2106.05(g), example (iv): Obtaining information about transactions). Therefore, the limitations of claims 6 and 7 do not amount to significantly more than the abstract idea.
Claims 8-10 are dependent on independent claim 1 and includes all the limitations of claim 1. The limitations of claim 8: “performing three-dimensional modeling” is recitation of Mathematical Concepts, because performing 3D mesh model is based on math or using math. Further, the limitation of claim 8 “acquiring a starting and ending diameter of the blood vessel” is recitation of Mere data gathering (See MPEP 2106.04(d) referencing MPEP 2106.05(g), example (iv): Obtaining information about transactions). The limitations of claim 9: “acquiring a blood vessel segment of interest” is recitation of Mere data gathering activity. Further, the limitations of claims 9 and 10: “picking up a starting point and an ending point of the blood vessel; picking up at least one seed point of the blood vessel segment” are recitations of Mental Processes using evaluation or judgement, since the claim language “picking up” is construed as determining/choosing an object (under BRI). The last limitations of claims 9 and 10: “segmenting a blood vessel partial area image …; segmenting the two-dimensional angiogram image …” are recitations of Mental Processes using pen and paper. Under BRI, anyone can segment or divide an image according to the requirement section or position. Therefore, the limitations of claims 8-10 do not amount to significantly more than the abstract idea.
Claims 11 and 12 are dependent on independent claim 1 and includes all the limitations of claim 1. The 1st part of 1st limitation in claim 11: “performing image enhancement processing for the blood vessel …” is recitation of Mental Processes using pen and paper, and 2nd part of 1st limitation in claim 11: “to obtain a sharply-contrasting rough image of the blood vessel” is recitation of Mere data gathering (See MPEP 2106.04(d) referencing MPEP 2106.05(g), example (iv): Obtaining information about transactions). Further the limitation of claim 11: “meshing the rough image of the blood vessel” is recitation of Mathematical Concepts, and the limitation: “extracting at least one blood vessel path line …” is recitation of Mere data gathering activity. The last limitation of claim 11: “selecting one blood vessel path line …” is recitation of Mental Processes using evaluation or judgement. The limitations in claim 12: “meshing the rough image of the blood vessel”; searching for a point having a shortest path in time … and repeating the above step for the third point until the shortest path in time reaches the ending point” are is recitations of Mathematical Concepts. Further, the last limitation of claim 12: “obtaining at least one blood vessel path line by connecting a line …” is recitation of Mere data gathering activity. Therefore, the limitations of claims 11 and 12 do not amount to significantly more than the abstract idea. Claims 13 and 14 are dependent on independent claim 1 and includes all the limitations of claim 1. The 1st limitation in claim 13: “summing a time taken for each path line of the blood vessel extending from the starting point to the ending point …” is recitation of Mental Processes using pen and paper. Under BRI, anyone can sum or add two or more path lines. Further, the last limitation of claim 13: “selecting the path line of the blood vessel with a shortest time …” is recitation of Mental Processes using evaluation or judgement. The limitations of claim 14: “performing image processing for the blood vessel partial area image to acquire an rough trend line of the blood vessel …; acquiring a rough edge line of the blood vessel, …; extracting the blood vessel centerline …” are recitations of Mere data gathering (See MPEP 2106.04(d) referencing MPEP 2106.05(g), example (iv): Obtaining information about transactions). Therefore, the limitations of claims 13 and 14 do not amount to significantly more than the abstract idea.
Claims 15-18 are dependent on independent claim 1 and includes all the limitations of claim 1. The 1st limitation in claim 15: “performing meshing for the blood vessel partial area image …; searching the blood vessel skeleton for a point … and repeating the above step for the third point until reaching the ending point, …” are recitations of Mathematical Concepts. The 2nd limitation in claim 15: “obtaining at least one connection line from the starting point to the ending point …” is recitation of Mere data gathering activity. The last limitation in claim 15: “selecting one connection line as the blood vessel centerline …” is recitation of Mental Processes using evaluation or judgement. The limitations of claims 16-18 are recitations of Mathematical Concepts. Therefore, the limitations of claims 15-17 do not amount to significantly more than the abstract idea.
SOFTWARE PER SE
Claims 18 and 19 are drawn to a device for synthesizing a mathematical model of a blood vessel and a coronary artery analysis system, respectively. The system could be interpreted to comprise only software elements. According to the current guidance, a system that qualifies as a patent eligible system under 35 USC 101 cannot consist only of software per se. If the system consists only of software per se, the system is not a patent eligible under 35 USC 101. Because the instant claims could comprise software per se, the limitation is only supported by software or computer program (as per Specification of current Application para [0080 and 00191]). Therefore, the claims 18 and 19 are being held as non-statutory under 35 USC 101. Please see MPEP 2106.03, which stated: “Products that do not have a physical or tangible form, such as information (often referred to as "data per se") or a computer program per se (often referred to as "software per se") when claimed as a product without any structural recitations”.
SIGNAL PER SE
Claim 20 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim does not fall within at least one of the four categories of patent eligible subject matter because the claims include “computer storage medium having stored thereon a computer program to be executed by a processor”. A review of Applicant’s Specification, para. [00192] stated: “each aspect of the present disclosure can be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, resident software, microcode, etc.), or a combination of hardware and software implementations, which here can be collectively referred to as "circuit", "module" or "system". Further, para [00194] stated: “The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium.” As the list is non-limiting and the language does not explicitly claim a “non-transitory machine readable medium”, under broadest reasonable interpretation in view of the Specification, the “computer storage medium” can include a signal which is storing the instructions and accessible by a processor. As such, MPEP 2106.03(II) states: “A claim whose BRI covers both statutory and non-statutory embodiments embraces subject matter that is not eligible for patent protection and therefore is directed to non-statutory subject matter.” “For example, the BRI of computer storage media can encompass non-statutory transitory forms of signal transmission, such as a propagating electrical or electromagnetic signal per se. See In re Nuijten, 500 F.3d 1346, 84 USPQ2d 1495 (Fed. Cir. 2007). When the BRI encompasses transitory forms of signal transmission, a rejection under 35 U.S.C. 101 as failing to claim statutory subject matter would be appropriate. Thus, a claim to a computer storage medium that can be a compact disc or a carrier wave covers a non-statutory embodiment and therefore should be rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. See, e.g., Mentor Graphics v. EVE-USA, Inc., 851 F.3d at 1294-95, 112 USPQ2d at 1134 (claims to a “computer storage medium” were non-statutory, because their scope encompassed both statutory random-access memory and non-statutory carrier waves).” Examiner respectfully suggests that amending the claims to more explicitly disclaim transitory medium, such as using “non-transitory machine readable medium” would overcome this rejection. Examiner notes that in view of the 101 rejections for signal per se, the “computer storage medium” is not construed as structure.
Therefore, the claims 1-20 are not patent eligible under 35 USC 101.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
11. Claims 1-3,5-13,17,18 and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by an NPL thesis “Patient-Specific Modeling of Geometry and Blood Flow in Large Arteries” by Luca Antiga (hereinafter Antiga).
Regarding Claim 1, Antiga teaches a method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis, comprising: (Antiga disclosed in page 103 section 6.1: “we introduce the problem of directly investigating local hemodynamics in the vessels of interest. … a reliable instrument for blood flow modeling at the patient-specific level is computational fluid dynamics (CFD), which consists in modeling blood flow by numerically solving the partial differential equations of fluid dynamics given the geometry of the domain and boundary conditions.” In page 130-131 section 7.4.3: “A promising approach for the imposition of boundary conditions to reconstructed arterial tracts is represented by the coupling of 3D models and lumped parameter models representing the systemic and pulmonary circulation by the electric analogy. … This approach is particularly attractive because it is in principle capable to account for the effect of local pathological conditions, such as stenoses or aneurysms, or surgical procedures, on the whole circulatory system, providing meaningful boundary conditions for the 3D problem.” Further, in page 136 section 7.6.2: “Patient-specific models of arterial tracts are rarely planar, so that such planes must be defined interactively in several locations. … Such problems can find a simple and effective solution in Lagrangian techniques. Massless, neutrally buoyant, non-diffusive particles are seeded at the model inlet, and their trajectory computed in the pulsatile flow environment by solving the ordinary differential equations … Equation 7.27 can be solved by means of standard ordinary differential equation integration methods, … Integration step is expressed as a fraction of characteristic length of the cell of the underlying domain mesh.”).
Antiga teaches performing three-dimensional modeling according to a real-time diameter Dt of a blood vessel, a length L of a blood vessel centerline and a stenotic section to form a three-dimensional model of the blood vessel having a stenotic lesion section; (Antiga disclosed in page 26 section 2.5.5: “Level sets can be successfully applied to blood vessel 3D modeling by performing the initialization inside the vessels of interest on angiographic images. Under the influence of the inflation term of Equation 2.22, single points turn into sphere-like shapes which eventually merge with their neighbors. Surfaces during evolution, as well as final model surface, can be extracted by contouring the 0 level set of F(x, t) using Marching Cubes algorithm, as shown in Figure 2.11 superimposed to a surface obtained by contouring with user-defined threshold.” In page 87-88 section 5.3.3: “The resulting centerline is a piecewise linear line defined on the Voronoi diagram, whose vertices lie on Voronoi polygon boundaries. Values of Voronoi sphere radius R(x) are therefore defined on centerlines, so that centerline points are associated with maximal inscribed spheres, as shown in Figure 5.10. Since centerlines were constructed to lie on local maxima of distance from the boundary, there is a tight connection between maximal sphere radius and minimum projection diameter used in clinical evaluation. In fact, classic angiographic vessel diameter evaluation is performed considering the minimum diameter obtained by measurements on different projections. If the vessel is convex in the neighborhood of the section of interest, our method provides the measure of the minimum vessel diameter with respect to the projection angle, as shown in Figure 5.11 … The availability of a robust method for centerline computation and diameter measurement as the one presented here allows to characterize blood vessel geometry in a synthetic way, therefore giving the opportunity of performing a study on a population of models.”
It has been discussed in page 24 above the equation 2.32 that the limit time step for explicit time integration is given by the CFL condition. Therefore, the disclosure “centerlines were constructed to lie on local maxima of distance from the boundary, there is a tight connection between maximal sphere radius and minimum projection diameter used in clinical evaluation” corresponds to claim element “real-time diameter Dt of a blood vessel, a length L of a blood vessel centerline”).
Antiga teaches performing N-gon meshing along a circumferential surface of the three-dimensional model of the blood vessel having the stenotic lesion section to form a single-layer mesh model where N ≥ 6; (Examiner would construe the claim element “N-gon meshing” as “hexahedral mesh model”, because the condition for the polygon (N ≥ 6) meshing being given by the Applicant. Antiga disclosed in page 105-106 section 6.2.1: “In this section we address the problem of finding a splitting criterion for a bifurcation such that the resulting branches are generalized cylinders. We will treat the case of a single Y bifurcation, for which the two child branches have a similar diameter, … we propose to perform a triangular-based prismatic cut around the bifurcation center perpendicularly to the bifurcation plane prior to split the branches. … The prismatic volume generated is also generalized cylinder, therefore it can be meshed by sweeping using hexahedral elements. The branch endcaps at the bifurcation are now made up of three parts, two semi-disks separated by a rectangle which is one side of the triangular-based prism. … Again, each two branches endcaps share a semi-disk. Moreover, the three side faces of the prism have the same nodal distribution, so that the nodal distribution on the endcaps must be the same for all three branches. See Figure 6.1 for an example of result.” Figure 6.1 shown “Automatic decomposition of a carotid bifurcation model based on approximate centerlines computed with the algorithm, and it is noted that the stenotic region is automatically identified and isolated for subsequent adequate meshing.
It has been discussed in page 26 section 2.5.5 that level sets can be successfully applied to blood vessel 3D modeling by performing the initialization inside the vessels of interest on angiographic images. Under the influence of the inflation term of Equation 2.22, single points turn into sphere-like shapes which eventually merge with their neighbors. Therefore, the disclosure above “the prismatic volume generated is also generalized cylinder, therefore it can be meshed by sweeping using hexahedral elements” reads the claim limitation “performing N-gon meshing along a circumferential surface of the three-dimensional model of the blood vessel having the stenotic lesion section to form a single-layer mesh model”).
Antiga teaches performing surface layering on the single-layer mesh model to form a double-layer mesh model, that is, the mathematical model of the blood vessel. (Antiga disclosed in page 24-25 section 2.5.4: “Embedding parametric deformable surface into a scalar function allows to drop global parameterization, achieving topology independence and great deformations, … Therefore complexity depends on 3D image size rather than on model surface size. … The sparse-field approach, solves this problem by tracking the set of voxels, called active set, intersected by the level set of interest (usually the 0 level set) at each time step (see Figure 2.8), as well as two layers of voxels around the active set, to compute the required derivatives. This way only voxels in the active set have to be updated, … One more advantage of the sparse-field approach is that 0 level set position can be estimated from the values of F(x) and ∇F(x) of the voxels in the active set, … To gain insight into the sparse-field approach, we first remind that at each time step t~, F(x, t~) can be modeled as the signed distance function ... Therefore, the active voxels must have a value of F(x, t~) ε [-1/2h, 1/2h], h being the voxel spacing, since the 0-level set must intersect the active voxels by definition. … the values of F for two layers of voxels on each side of the active set are provided. Voxel values for each inner (or outer) layer are computed from the value of the voxels of the neighboring layer by subtracting (or adding) h to the minimum (or maximum) valued neighbor. Therefore, in the sparse field approach, the embedding function is locally reinitialized to the signed distance function at every iteration.”
The disclosures “The sparse-field approach, solves this problem by tracking the set of voxels, called active set, intersected by the level set of interest usually the 0 level set, at each time step (see Figure 2.8), as well as two layers of voxels around the active set”; “the values of F for two layers of voxels on each side of the active set are provided” teach the limitation “performing surface layering on the single-layer mesh model to form a double-layer mesh model”).
Regarding claim 2, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 1, wherein a manner for performing N-gon meshing along a circumferential surface of the three-dimensional model of the blood vessel having the stenotic lesion section to form a single-layer mesh model where N ≥ 6 comprises: performing meshing using a triangle as a smallest unit along a circumferential surface of the three-dimensional model of the blood vessel having the stenotic lesion section; (Antiga disclosed in page 118 section 6.3.2: “After the creation of boundary layers of wedges having thickness automatically adapted to vessel size, the last step is to fill the inner volume with quadratic 10-node tetrahedra (see Figure 6.9 and Figure 6.10). For this mean we use the advancing front tetrahedral meshing scheme … Advancing front schemes work by adding elements from the boundary (the initial front) to the interior of the domain ... In our case the initial front is represented by the warped surface mesh. Each triangle of the front is assigned a priority value. Elements are added by selecting the triangle with the highest priority, removing it from the front, forming a new tetrahedron by inserting a new point in an appropriate position in the vicinity of the selected triangle, and updating the front”. Figure 6.1 shown “Automatic decomposition of a carotid bifurcation model based on approximate centerlines computed with the algorithm, and it is noted that the stenotic region is automatically identified and isolated for subsequent adequate meshing.).
Antiga teaches sequentially combining and converting every N triangles into a N-gon to form an initial N-gon mesh; (Antiga disclosed in page 118 section 6.3.2: “After the creation of boundary layers of wedges having thickness automatically adapted to vessel size, the last step is to fill the inner volume with quadratic 10-node tetrahedra (see Figure 6.9 and Figure 6.10). For this mean we use the advancing front tetrahedral meshing scheme … Advancing front schemes work by adding elements from the boundary (the initial front) to the interior of the domain ... In our case the initial front is represented by the warped surface mesh. Each triangle of the front is assigned a priority value. Elements are added by selecting the triangle with the highest priority, removing it from the front, forming a new tetrahedron by inserting a new point in an appropriate position in the vicinity of the selected triangle, and updating the front. … A number of tests must be performed on the neighborhood when a new point has to be inserted. Gambit employs a meshing scheme in which Delaunay criterion is used to ensure that the new point is properly inserted.”).
Antiga teaches removing connection lines inside each N-gon in the initial N-gon mesh to form a single-layer N-gon mesh model, where N ≥ 6. (Antiga disclosed in page 118 section 6.3.2: “After the creation of boundary layers of wedges having thickness automatically adapted to vessel size, the last step is to fill the inner volume with quadratic 10-node tetrahedra (see Figure 6.9 and Figure 6.10). For this mean we use the advancing front tetrahedral meshing scheme … Advancing front schemes work by adding elements from the boundary (the initial front) to the interior of the domain ... In our case the initial front is represented by the warped surface mesh. Each triangle of the front is assigned a priority value. Elements are added by selecting the triangle with the highest priority, removing it from the front, forming a new tetrahedron by inserting a new point in an appropriate position in the vicinity of the selected triangle, and updating the front.”).
Regarding claim 3, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 2, wherein a manner for performing meshing using a triangle as the smallest unit along a circumferential surface of the three-dimensional model of the blood vessel having the stenotic lesion section comprises: segmenting the three-dimensional model of the blood vessel having the stenotic lesion section into K segments, (Antiga disclosed in page 11-12 section 2.3 to 2.3.1: “the simplest approach for the reconstruction of 3D models representing the vessel wall is the creation of a surface in correspondence of a given gray level of the acquired 3D image volume (see Figure 2.3). … Marching Cubes will be employed both for the initialization and as a final step of level sets-based reconstruction, our major instrument for blood vessel modeling. … The base concept of the Marching Cubes algorithm is that the above and below voxels of each cube can be partitioned by a set of triangles whose vertices lie on cube edges in a finite number of ways, called cases. Therefore a table of cases can be constructed, containing all topological configurations of above and below voxels and triangles partitioning them, regardless the exact position of triangle vertices along cube edges (as in Figure 2.4, which only has a topological meaning.”).
Antiga teaches performing meshing using a triangle as the smallest unit on a circumferential surface of each segment of the three-dimensional model of the blood vessel. (Antiga disclosed in page 118 section 6.3.2: “After the creation of boundary layers of wedges having thickness automatically adapted to vessel size, the last step is to fill the inner volume with quadratic 10-node tetrahedra (see Figure 6.9 and Figure 6.10). For this mean we use the advancing front tetrahedral meshing scheme … Advancing front schemes work by adding elements from the boundary (the initial front) to the interior of the domain ... In our case the initial front is represented by the warped surface mesh. Each triangle of the front is assigned a priority value. Elements are added by selecting the triangle with the highest priority, removing it from the front, forming a new tetrahedron by inserting a new point in an appropriate position in the vicinity of the selected triangle, and updating the front”. Figure 6.1 shown “Automatic decomposition of a carotid bifurcation model based on approximate centerlines computed with the algorithm, and it is noted that the stenotic region is automatically identified and isolated for subsequent adequate meshing.).
Regarding claim 5, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 1, wherein a manner for performing surface layering on the single-layer mesh model to form a double-layer mesh model, that is, the mathematical model of the blood vessel, comprises: acquiring a blood vessel wall thickness h; (Antiga disclosed in page 114 section 6.3.1: “we presented a method to compute a measure of the distance of surface points to centerlines. In particular, the geodesic distance of surface points to centerlines computed on the embedded Voronoi diagram was calculated … The geodesic distance of a surface point p to centerlines was then defined as Dg(p) … The availability of Dg allows to define boundary layer thickness as a fraction of vessel size, …”).
Antiga teaches performing three-dimensional modeling according to the blood vessel wall thickness h, a starting diameter Dstarting of the blood vessel, an ending diameter Dending of the blood vessel and the length L of the blood vessel centerline to form a truncated cone three-dimensional model on an inner surface or an outer surface of the single-layer mesh model; (Under BRI and conventional meaning in the art Examiner would construe the claim element “truncated cone” as stenotic region of blood vessel.
Antiga disclosed in page 26 section 2.5.5: “Level sets can be successfully applied to blood vessel 3D modeling by performing the initialization inside the vessels of interest on angiographic images. Under the influence of the inflation term of Equation 2.22, single points turn into sphere-like shapes which eventually merge with their neighbors. Surfaces during evolution, as well as final model surface, can be extracted by contouring the 0 level set of F(x, t) using Marching Cubes algorithm, as shown in Figure 2.11 superimposed to a surface obtained by contouring with user-defined threshold.” In page 87-88 section 5.3.3: “The resulting centerline is a piecewise linear line defined on the Voronoi diagram, whose vertices lie on Voronoi polygon boundaries. Values of Voronoi sphere radius R(x) are therefore defined on centerlines, so that centerline points are associated with maximal inscribed spheres, as shown in Figure 5.10. Since centerlines were constructed to lie on local maxima of distance from the boundary, there is a tight connection between maximal sphere radius and minimum projection diameter used in clinical evaluation. In fact, classic angiographic vessel diameter evaluation is performed considering the minimum diameter obtained by measurements on different projections. If the vessel is convex in the neighborhood of the section of interest, our method provides the measure of the minimum vessel diameter with respect to the projection angle, as shown in Figure 5.11 …”. Further, Figure 2.13 F shown “highly stenotic internal carotid artery reconstruction”; Figure 6.1 shown the “stenotic region is automatically identified and isolated for subsequent adequate meshing”; Figure 6.4 Left shown “hexahedral mesh for the stenotic carotid bifurcation model”).
Antiga teaches performing N-gon meshing along a circumferential surface of the truncated cone three-dimensional model according to a manner for acquiring the single-layer mesh model, to form another single-layer mesh model; (Antiga disclosed in page 105-106 section 6.2.1: “In this section we address the problem of finding a splitting criterion for a bifurcation such that the resulting branches are generalized cylinders. We will treat the case of a single Y bifurcation, for which the two child branches have a similar diameter, … we propose to perform a triangular-based prismatic cut around the bifurcation center perpendicularly to the bifurcation plane prior to split the branches. … The prismatic volume generated is also generalized cylinder, therefore it can be meshed by sweeping using hexahedral elements. The branch endcaps at the bifurcation are now made up of three parts, two semi-disks separated by a rectangle which is one side of the triangular-based prism. … Again, each two branches endcaps share a semi-disk. Moreover, the three side faces of the prism have the same nodal distribution, so that the nodal distribution on the endcaps must be the same for all three branches. See Figure 6.1 for an example of result.” Figure 6.1 shown “Automatic decomposition of a carotid bifurcation model based on approximate centerlines computed with the algorithm, and it is noted that the stenotic region is automatically identified and isolated for subsequent adequate meshing.
It has been discussed in page 26 section 2.5.5 that level sets can be successfully applied to blood vessel 3D modeling by performing the initialization inside the vessels of interest on angiographic images. Under the influence of the inflation term of Equation 2.22, single points turn into sphere-like shapes which eventually merge with their neighbors. Therefore, the disclosure above “the prismatic volume generated is also generalized cylinder, therefore it can be meshed by sweeping using hexahedral elements” reads the claim limitation “performing N-gon meshing along a circumferential surface of the three-dimensional model of the blood vessel having the stenotic lesion section to form a single-layer mesh model”).
Antiga teaches forming a double-layer mesh model, that is, the mathematical model of the blood vessel, by using two layers of the single-layer mesh model and the blood vessel wall thickness h. (Antiga disclosed in page 24-25 section 2.5.4: “Embedding parametric deformable surface into a scalar function allows to drop global parameterization, achieving topology independence and great deformations, … Therefore complexity depends on 3D image size rather than on model surface size. … The sparse-field approach, solves this problem by tracking the set of voxels, called active set, intersected by the level set of interest (usually the 0 level set) at each time step (see Figure 2.8), as well as two layers of voxels around the active set, to compute the required derivatives. This way only voxels in the active set have to be updated, … One more advantage of the sparse-field approach is that 0 level set position can be estimated from the values of F(x) and ∇F(x) of the voxels in the active set, … To gain insight into the sparse-field approach, we first remind that at each time step t~, F(x, t~) can be modeled as the signed distance function ... Therefore, the active voxels must have a value of F(x, t~) ε [-1/2h, 1/2h], h being the voxel spacing, since the 0-level set must intersect the active voxels by definition. … the values of F for two layers of voxels on each side of the active set are provided. Voxel values for each inner (or outer) layer are computed from the value of the voxels of the neighboring layer by subtracting (or adding) h to the minimum (or maximum) valued neighbor. Therefore, in the sparse field approach, the embedding function is locally reinitialized to the signed distance function at every iteration.” In in page 114 section 6.3.1: “we presented a method to compute a measure of the distance of surface points to centerlines. In particular, the geodesic distance of surface points to centerlines computed on the embedded Voronoi diagram was calculated … The geodesic distance of a surface point p to centerlines was then defined as Dg(p) … The availability of Dg allows to define boundary layer thickness as a fraction of vessel size, …”).
Regarding claim 6, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 1, wherein a manner for performing three-dimensional modeling according to a real-time diameter Dt of a blood vessel, a length L of a blood vessel centerline and a stenotic section to form a three-dimensional model of the blood vessel having a stenotic lesion section comprises: acquiring two-dimensional coronary artery angiogram images of at least two body positions; (Antiga disclosed in page 59 section 4.4.1: “Branching vessels can be ignored when they have a small diameter with respect to acquisition resolution, so that reconstruction is not possible, … An example of the first case is the abdominal aorta, where the inferior mesenteric artery is often not reconstructible from MR angiography images due to its dimensions. The second case can be encountered at the branching vessels of the external carotid artery, the superior thyroid artery, the lingual artery, the occipital artery and the external maxillary artery.”).
Antiga teaches obtaining a real-time diameter Dt of the blood vessel and the length L of a straightened blood vessel centerline according to the two-dimensional coronary artery angiogram images; (Antiga disclosed in page 87-88 section 5.3.3: “The resulting centerline is a piecewise linear line defined on the Voronoi diagram, whose vertices lie on Voronoi polygon boundaries. Values of Voronoi sphere radius R(x) are therefore defined on centerlines, so that centerline points are associated with maximal inscribed spheres, as shown in Figure 5.10. Since centerlines were constructed to lie on local maxima of distance from the boundary, there is a tight connection between maximal sphere radius and minimum projection diameter used in clinical evaluation. In fact, classic angiographic vessel diameter evaluation is performed considering the minimum diameter obtained by measurements on different projections.” The disclosure “centerlines were constructed to lie on local maxima of distance from the boundary, there is a tight connection between maximal sphere radius and minimum projection diameter used in clinical evaluation” corresponds to claim limitation “obtaining a real-time diameter Dt of the blood vessel and the length L of a straightened blood vessel centerline according to the two-dimensional coronary artery angiogram images”).
Antiga teaches performing three-dimensional modeling according to the Dt and L to form a truncated cone three-dimensional model; acquiring the stenotic section of the coronary artery; (Antiga disclosed in page 104-105 section 6.2: “Hexahedral elements are usually employed in CFD when it is possible to orientate them along the expected direction of flow. In these cases numerical solutions are characterized by quick convergence and good accuracy … Mesh generation tools implemented in commercial applications are usually tailored to deal with CAD models. … In this section we present an approach based on automatically splitting of the models to discretize into generalized cylinders (this phase is implemented outside Gambit) and generating the mesh for each branch by sweeping …”. In page 106 section 6.2.1: “we propose to perform a triangular-based prismatic cut around the bifurcation center perpendicularly to the bifurcation plane prior to split the branches. … The bifurcation plane is used as a reference for the construction of all cutting planes. The prismatic cut is performed with three planes normal to the bifurcation plane and to each afferent branch centerline, at a distance from bifurcation barycenter set as a fraction of the radius of the sphere enclosing the bifurcation. The intersections of each two planes together with the midpoint of the shortest segment between the respective enclosing sphere-model intersection profiles are then used to identify three more cutting planes. … The branch endcaps at the bifurcation are now made up of three parts, two semi-disks separated by a rectangle which is one side of the triangular-based prism. Again, each two branches endcaps share a semi-disk. … See Figure 6.1 for an example of result.”
Figure 6.1 shown “Automatic decomposition of a carotid bifurcation model based on approximate centerlines computed with the algorithm. The stenotic region is noticed, which is automatically identified and isolated for subsequent adequate meshing. Further, Figure 6.3 shown the “visualization of the volume mesh resulting from Cooper scheme meshing of the single subparts. Cross-sectional node distribution is well-preserved along the branches, even in the highly stenotic tract, with boundary layer thickness correctly scaling with vessel diameter, and well-shaped elements are obtained in the branching region around the triangular-based prism cut. Figure 6.4 at left shown hexahedral mesh for the stenotic carotid bifurcation model, right side shown particular of the discretization obtained at the bifurcation apex).
Antiga teaches projecting the stenotic section onto the truncated cone three-dimensional model correspondingly to obtain a three-dimensional model of the blood vessel having a stenotic lesion section. (Antiga disclosed in page 109-112: “The last step of mesh generation is the creation of internal nodes and elements, which is the core of the Cooper algorithm. … From our experience, the algorithm results to be very effective in preserving cross-sectional node distribution even in regions of high stenosis grade, as shown in Figure 6.3. … Therefore, the meshes generated by the described approach meet the requirements of being well-aligned with the expected direction of flow and presenting scale-dependent boundary layers. The resulting volume elements are linear hexahedra of high quality. Figure 6.4 shows the final hexahedral mesh for the stenotic carotid bifurcation considered in this section, while Figure 6.5 shows the hexahedral mesh for the controlateral carotid bifurcation model obtained from the same acquisition.” Figure 6.3 shown the “visualization of the volume mesh resulting from Cooper scheme meshing of the single subparts. Cross-sectional node distribution is well-preserved along the branches, even in the highly stenotic tract, with boundary layer thickness correctly scaling with vessel diameter, and well-shaped elements are obtained in the branching region around the triangular-based prism cut. Figure 6.4 at left shown hexahedral mesh for the stenotic carotid bifurcation model, right side shown particular of the discretization obtained at the bifurcation apex).
Regarding claim 7, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 6, wherein a manner for performing three-dimensional modeling according to a real-time diameter Dt of a blood vessel and the length L of a straightened blood vessel centerline according to the two-dimensional coronary artery angiogram images comprises: extracting a blood vessel centerline from the two-dimensional coronary artery angiogram image of each body position along a direction from an inlet of the coronary artery to an end of the coronary artery; (Antiga disclosed in page 87-88 section 5.3.3: “The resulting centerline is a piecewise linear line defined on the Voronoi diagram, whose vertices lie on Voronoi polygon boundaries. Values of Voronoi sphere radius R(x) are therefore defined on centerlines, so that centerline points are associated with maximal inscribed spheres, as shown in Figure 5.10. Since centerlines were constructed to lie on local maxima of distance from the boundary, there is a tight connection between maximal sphere radius and minimum projection diameter used in clinical evaluation. In fact, classic angiographic vessel diameter evaluation is performed considering the minimum diameter obtained by measurements on different projections.” In page 144 section 7.7.2: “Blood was modeled as Newtonian … Vessel wall was assumed rigid. Boundary conditions were imposed as time-varying parabolic velocity profiles on the aorta inlet and on the celiac, superior mesenteric, right and left renal outlets, on the basis of the mean blood flow values … while zero traction was imposed on the aorta outlet. Flow waveform for the aorta inlet was taken from (shown in Figure 7.7). The flow waveforms for celiac, superior mesenteric, right and left renal were obtained by appropriately scaling the aorta inlet flow waveform …”).
Antiga teaches obtaining an image of a straightened blood vessel according to the two-dimensional coronary artery angiogram image and the blood vessel centerline; (Antiga disclosed in page 87 section 5.3.3: “The resulting centerline is a piecewise linear line defined on the Voronoi diagram, whose vertices lie on Voronoi polygon boundaries. Values of Voronoi sphere radius R(x) are therefore defined on centerlines, so that centerline points are associated with maximal inscribed spheres, as shown in Figure 5.10. Since centerlines were constructed to lie on local maxima of distance from the boundary, there is a tight connection between maximal sphere radius and minimum projection diameter used in clinical evaluation. In fact, classic angiographic vessel diameter evaluation is performed considering the minimum diameter obtained by measurements on different projections.” In page 91-93 section 5.4.1-5.4.2: “The computation of the minimum distance of poles to centerlines measured on the Voronoi diagram is a geodesic distance computation problem, … geodesic distances are obtained by solving the following Eikonal equation, where F(x)= 1 … VorE(P) is the embedded Voronoi diagram, and P is the set of surface points. The boundary conditions are here expressed by zero values on centerline points. The solution to this problem is found once again applying the fast marching method for polygonal non-manifolds (see Figure 5.14 left). … The correspondence can be retrieved constructing geodesic paths on the Voronoi diagram from surface points (more correctly, from the associated poles) to the centerlines. … this is done tracing a path from each pole following the steepest descent of the geodesic distance field T~(x), therefore solving Equation 5.12, until centerlines are encountered.”).
Antiga teaches obtaining a straightened blood vessel contour line according to the straightened blood vessel centerline and the image of the straightened blood vessel; (Antiga disclosed in page 26 section 2.5.5: “Level sets can be successfully applied to blood vessel 3D modeling by performing the initialization inside the vessels of interest on angiographic images. … Surfaces during evolution, as well as final model surface, can be extracted by contouring the 0 level set of F(x,t) using Marching Cubes algorithm, as shown in Figure 2.11 superimposed to a surface obtained by contouring with user-defined threshold. Figure 2.12 shown the “Evolution of the 0-level set plotted on the source image (upper left) and on its gradient modulus (upper right). The two inner contours correspond to the inflation phase”. Further, in page 30 (last para in section 2.5: “since evolution parameters are dependent on vessel scale, we let level sets evolve into single vessels, or into groups of vessels of similar scale … we then merge the Fi(x) functions resulting from N single vessel evolutions, and finally extract model surface by contouring the merged Fm(x) function with Marching Cubes algorithm. … An example of single vessel evolution and merging for a carotid bifurcation is depicted in Figure 2.13, while the intersections of model points with gradient magnitude images in the region of the bifurcation apex are shown in Figure 2.14.”).
Antiga teaches acquiring geometric information of the straightened blood vessel, comprising: the real-time diameter Dt of the blood vessel, and the length of the straightened blood vessel centerline, that is, the length L of the centerline of the straightened blood vessel. (Antiga disclosed in page 87-88 section 5.3.3: “The resulting centerline is a piecewise linear line defined on the Voronoi diagram, whose vertices lie on Voronoi polygon boundaries. Values of Voronoi sphere radius R(x) are therefore defined on centerlines, so that centerline points are associated with maximal inscribed spheres, as shown in Figure 5.10. Since centerlines were constructed to lie on local maxima of distance from the boundary, there is a tight connection between maximal sphere radius and minimum projection diameter used in clinical evaluation. In fact, classic angiographic vessel diameter evaluation is performed considering the minimum diameter obtained by measurements on different projections.” The disclosure “centerlines were constructed to lie on local maxima of distance from the boundary, there is a tight connection between maximal sphere radius and minimum projection diameter used in clinical evaluation” corresponds to claim limitation “acquiring a real-time diameter Dt of the blood vessel and the length L of the centerline of the straightened blood vessel”).
Regarding claim 8, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 6, wherein a manner for performing three-dimensional modeling according to and L to form a truncated cone three-dimensional model comprises: performing three-dimensional modeling according to the geometric information, the centerline and the contour line to obtain a three-dimensional model of the blood vessel having a stenotic lesion section; (Antiga disclosed in page 26 section 2.5.5: “Level sets can be successfully applied to blood vessel 3D modeling by performing the initialization inside the vessels of interest on angiographic images. … Surfaces during evolution, as well as final model surface, can be extracted by contouring the 0 level set of F(x,t) using Marching Cubes algorithm, as shown in Figure 2.11 superimposed to a surface obtained by contouring with user-defined threshold. Figure 2.12 shown the “Evolution of the 0-level set plotted on the source image (upper left) and on its gradient modulus (upper right). The two inner contours correspond to the inflation phase”. Further, in page 30 (last para in section 2.5: “since evolution parameters are dependent on vessel scale, we let level sets evolve into single vessels, or into groups of vessels of similar scale … we then merge the Fi(x) functions resulting from N single vessel evolutions, and finally extract model surface by contouring the merged Fm(x) function with Marching Cubes algorithm. … An example of single vessel evolution and merging for a carotid bifurcation is depicted in Figure 2.13, while the intersections of model points with gradient magnitude images in the region of the bifurcation apex are shown in Figure 2.14.”).
Antiga teaches acquiring a starting diameter Dstarting of the blood vessel and an ending diameter Dending of the blood vessel from the real-time diameter Dt of the blood vessel; (Antiga disclosed in page 26 section 2.5.5: “Level sets can be successfully applied to blood vessel 3D modeling by performing the initialization inside the vessels of interest on angiographic images. Under the influence of the inflation term of Equation 2.22, single points turn into sphere-like shapes which eventually merge with their neighbors. Surfaces during evolution, as well as final model surface, can be extracted by contouring the 0 level set of F(x, t) using Marching Cubes algorithm, as shown in Figure 2.11 superimposed to a surface obtained by contouring with user-defined threshold.” In page 39 1st para: “referring to Figure 3.2, the algorithm starts with the identification of the open profiles of the vessel structure, i.e. the inlet and outlet section profiles. … Once one profile is chosen, its barycenter is calculated. Since profiles are piecewise linear lines, their barycenter is computed taking into account the segments connecting polyline vertices by weighting point positions with the half-length of their neighboring segments. The probing sphere is then defined with the center cs on the barycenter b of the defining profile P, and with a radius equal to
rs = k dmax … At this point, the intersection of the sphere with the surface connected to the defining profile is calculated. This is done by iteratively visiting neighboring surface mesh vertices starting from the defining profile …”).
Antiga teaches performing three-dimensional modeling according to the Dstarting, Dending and L to form a truncated cone three-dimensional model. (Antiga disclosed in page 87-88 section 5.3.3: “The resulting centerline is a piecewise linear line defined on the Voronoi diagram, whose vertices lie on Voronoi polygon boundaries. Values of Voronoi sphere radius R(x) are therefore defined on centerlines, so that centerline points are associated with maximal inscribed spheres, as shown in Figure 5.10. Since centerlines were constructed to lie on local maxima of distance from the boundary, there is a tight connection between maximal sphere radius and minimum projection diameter used in clinical evaluation. In fact, classic angiographic vessel diameter evaluation is performed considering the minimum diameter obtained by measurements on different projections. If the vessel is convex in the neighborhood of the section of interest, our method provides the measure of the minimum vessel diameter with respect to the projection angle, as shown in Figure 5.11 …”. Further, Figure 2.13 F shown “highly stenotic internal carotid artery reconstruction”; Figure 6.1 shown the “stenotic region is automatically identified and isolated for subsequent adequate meshing”; Figure 6.4 Left shown “hexahedral mesh for the stenotic carotid bifurcation model”).
Regarding claim 9, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 6, after acquiring two-dimensional coronary artery angiogram images of at least two body positions, and before obtaining a starting diameter Dstarting of the blood vessel and an ending diameter Dending of the blood vessel from the real-time diameter Dt of the blood vessel and the length L of a straightened blood vessel centerline according to the two-dimensional coronary artery angiogram images, further comprising: acquiring a blood vessel segment of interest from the two-dimensional coronary artery angiogram image; (Antiga disclosed in page 11-12 section 2.3 to 2.3.1: “the simplest approach for the reconstruction of 3D models representing the vessel wall is the creation of a surface in correspondence of a given gray level of the acquired 3D image volume (see Figure 2.3). … Marching Cubes will be employed both for the initialization and as a final step of level sets-based reconstruction, our major instrument for blood vessel modeling. … The base concept of the Marching Cubes algorithm is that the above and below voxels of each cube can be partitioned by a set of triangles whose vertices lie on cube edges in a finite number of ways, called cases. Therefore a table of cases can be constructed, containing all topological configurations of above and below voxels and triangles partitioning them, regardless the exact position of triangle vertices along cube edges (as in Figure 2.4, which only has a topological meaning.”).
Antiga teaches picking up a starting point and an ending point of the blood vessel segment of interest; (Antiga disclosed in page 39-41: “referring to Figure 3.2, the algorithm starts with the identification of the open profiles of the vessel structure, i.e. the inlet and outlet section profiles. … Once intersection profiles are reconstructed, they can be counted. If one new profile is generated, the surface between the defining and the new profile is a topological cylinder, therefore the new profile is taken as defining profile, and a new step is performed. If no profiles are generated, a dead end of a vessel segment has been found, so the set of probing sphere centers are stored as a vessel segment and the analysis continues with a new segment from an available (i.e. not visited) profile. If two or more profiles are generated, the surface contained in the sphere is a bifurcation, therefore the vessel segment is stored, and the new profiles are made available. It can also happen that during point visiting procedure an available profile is encountered. This means that the current segment ends on a bifurcation which has been already identified, or on an outlet of the model.”).
Antiga teaches segmenting a blood vessel partial area image corresponding to the starting point and the ending point from the two-dimensional coronary artery angiogram image. (Antiga disclosed in page 40-41: “Once intersection profiles are reconstructed, they can be counted. If one new profile is generated, the surface between the defining and the new profile is a topological cylinder, therefore the new profile is taken as defining profile, and a new step is performed. If no profiles are generated, a dead end of a vessel segment has been found, so the set of probing sphere centers are stored as a vessel segment and the analysis continues with a new segment from an available (i.e. not visited) profile. If two or more profiles are generated, the surface contained in the sphere is a bifurcation, therefore the vessel segment is stored, and the new profiles are made available. It can also happen that during point visiting procedure an available profile is encountered. This means that the current segment ends on a bifurcation which has been already identified, or on an outlet of the model. Each time a bifurcation is encountered, it is assigned a unique id, and its profiles are marked with it. This way, whenever a segment has been constructed, its endpoints are associated with the id of the bifurcations enclosing it. Therefore vascular network topology can be reconstructed without the need of any particular order in visiting segments. During the analysis of segments, an estimate of mean radius is calculated at each step of the probing sphere by computing the mean distance of the points visited at that step from the line defined by the barycenter of the defining and the intersection profiles, which approximates vessel centerline. For bifurcations, the barycenter of the bifurcation surface is calculated, and it is joined to the endpoints of the afferent branches.”).
Regarding claim 10, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 9, wherein a manner for segmenting a blood vessel partial area image corresponding to the starting point and the ending point from the two-dimensional coronary artery angiogram image further comprises: picking up at least one seed point of the blood vessel segment of interest; (Antiga disclosed in page 71-73: “The Voronoi diagram of a point set P is dual to the Delaunay tessellation of P, DelP, which is a tetrahedrization of point set P which satisfies the property that the sphere circumscribed to each tetrahedron … The relationship between Voronoi diagram and Delaunay tetrahedra holds in that Voronoi vertices are the circumcenters of Delaunay tetrahedra, and the spheres circumscribed to Delaunay tetrahedra, called Voronoi spheres, are maximal spheres with respect to point set P. … in order to obtain medial axis approximation from the Voronoi diagram, a subset of the Voronoi diagram internal to the object must be selected, here referred as embedded Voronoi diagram. … it is necessary to compute surface normals at surface mesh vertices, orientate them outward (this is done propagating the orientation from a outward-oriented seed neighborhood throughout the mesh), …”. In page 74 Figure 5.5 at Left shown “abdominal aorta model surface” and at Right “embedded Voronoi diagram (colored surface) and internal Delaunay tetrahedra boundary (transparent surface). Colors map R, which is the radius of Voronoi spheres.”).
Antiga teaches segmenting the two-dimensional angiogram image between two adjacent points of the starting point, the seed point and the ending point, respectively, to obtain at least two blood vessel partial area images. (Antiga disclosed in page 86-87: “the whole Voronoi diagram with the pole associated to the barycenter of an inlet section as the seed point, centerlines are obtained by backtracing a path along the direction of maximum descent of Tx (Equation 5.12) starting from each of the poles associated to the barycenter of the remaining sections. … One advantage of our method, besides being fast, is that centerline vertices are defined on Voronoi polygon boundaries only. … The resulting centerline is a piecewise linear line defined on the Voronoi diagram, whose vertices lie on Voronoi polygon boundaries. Values of Voronoi sphere radius Rx are therefore defined on centerlines, so that centerline points are associated with maximal inscribed spheres, as shown in Figure 5.10. Since centerlines were constructed to lie on local maxima of distance from the boundary, there is a tight connection between maximal sphere radius and minimum projection diameter used in clinical evaluation [136]. In fact, classic angiographic vessel diameter evaluation is performed considering the minimum diameter obtained by measurements on different projections.” Figure 5.10 at Left shown: “solution of the Eikonal equation over the embedded Voronoi diagram for the abdominal aorta model presented in Figure 5.5, with seed point at the aorta inlet.” And at Right: “centerlines obtained after backtracing from model outlets (namely aorta outlet, renal, superior mesenteric and celiac arteries).”).
Regarding claim 11, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 7, wherein a manner for extracting a blood vessel centerline from the two-dimensional coronary artery angiogram image of each body position along a direction from an inlet of the coronary artery to an end of the coronary artery comprises: performing image enhancement processing for the blood vessel partial area images to obtain a sharply-contrasting rough image of the blood vessel; (Antiga disclosed in page 7-8 section 2.2.1: “Computed tomography (CT) is a technique for imaging cross-sections of a subject using series of X-ray measurements taken at different angles around the subject. … For vascular imaging, radio-opaque contrast is injected intravenously. The HU values yielded by contrast agents are positive values between that of connective tissue and that of calcium. Therefore, an artery affected by atherosclerotic plaques will be surrounded by connective tissue values and low contrast (lipid pools) and high contrast (calcified plaques) regions (see Figure 2.1). Although widely employed in the clinical practice, …”).
Antiga teaches meshing the rough image of the blood vessel, and extracting at least one blood vessel path line along a direction from the starting point to the ending point; (Antiga disclosed in page 39-40: “referring to Figure 3.2, the algorithm starts with the identification of the open profiles of the vessel structure, i.e. the inlet and outlet section profiles. … Once one profile is chosen, its barycenter is calculated. Since profiles are piecewise linear lines, their barycenter is computed taking into account the segments connecting polyline vertices … At this point, the intersection of the sphere with the surface connected to the defining profile is calculated. This is done by iteratively visiting neighboring surface mesh vertices starting from the defining profile and checking … where p is the position of a generic surface mesh vertex. … Once intersection profiles are reconstructed, they can be counted. If one new profile is generated, the surface between the defining and the new profile is a topological cylinder, therefore the new profile is taken as defining profile, and a new step is performed. If no profiles are generated, a dead end of a vessel segment has been found, so the set of probing sphere centers are stored as a vessel segment … It can also happen that during point visiting procedure an available profile is encountered. This means that the current segment ends on a bifurcation which has been already identified, or on an outlet of the model.”).
Antiga teaches selecting one blood vessel path line as the blood vessel centerline. (Antiga disclosed in page 44 section 3.5.1 (2nd para): “microvascular network endothelial surface can be reconstructed by first segmenting a volume of histological section 2D images, which must be performed under operator supervision given the variability of histological images and the importance of detecting the whole luminal space, and then by contouring the segmented volume with an algorithm such as Marching Cubes. The reconstructed surface can then be processed with the described algorithm, after opening the surface at one or more network inlets to create a starting profile. As a result, a 3D network of interconnecting centerlines is obtained (see Figure 3.6 A), with associated mean radius values.” In page 77-78 section 5.3.1: “From the given definition of centerlines it follows that centerlines must lie on the ridges of the distance transform associated with the tubular surface, therefore on its medial axis. For this reason our approach is that of looking for centerlines on the approximation of the medial axis of blood vessel surface given in terms of inner Voronoi diagram. To do that we formulate the centerline calculation problem in terms of energy minimization. We look for the path C= C(s) (s being arc length) traced from two points p0 and p1 which minimizes the following energy functional … Centerlines can in fact be viewed as deformable lines traced between two fixed points finding their stable configuration at a minimum of Ecenterline.”).
Regarding claim 12, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 11, wherein a manner for meshing the rough image of the blood vessel. and extracting at least one blood vessel path line along a direction from the starting point to the ending point comprises: meshing the rough image of the blood vessel; (Antiga disclosed in page 39-40: “referring to Figure 3.2, the algorithm starts with the identification of the open profiles of the vessel structure, i.e. the inlet and outlet section profiles. … Once one profile is chosen, its barycenter is calculated. Since profiles are piecewise linear lines, their barycenter is computed taking into account the segments connecting polyline vertices … At this point, the intersection of the sphere with the surface connected to the defining profile is calculated. This is done by iteratively visiting neighboring surface mesh vertices starting from the defining profile and checking … where p is the position of a generic surface mesh vertex.”).
Antiga teaches along a blood vessel extension direction from the starting point to the ending point, searching for a point having a shortest path in time with the starting point as a second point from intersecting points of surrounding n meshes, and searching for a point having a shortest path in time with the second point as a third point from intersecting points of surrounding n meshes, and repeating the above step for the third point until the shortest path in time reaches the ending point, where n is a positive integer greater than or equal to 1; (Antiga disclosed in page 79-80: “minimization Ecenterline in Equation 5.6 can be also achieved by computing the shortest path on the Voronoi diagram domain between p0 and p1 according to the metric induced by F(x) (setting F(x)=1 yields classic geodesics computed on surface metric). With this approach it is possible to directly extract the global minimum of Ecenterline. In the weighted geodesic approach, once a scalar field is defined on the domain, the aim is to find the path from p0 to p1 for which the integral of the scalar field along the path is minimal (for this reason the path is also called minimal cost or minimal action path). One way to solve this problem is that of defining the weighted geodesic distance of each point of the domain to point p0, and then to trace the path back from p1 to p0 along the gradient of weighted geodesic distance field … Since the scalar field T(x) represents weighted geodesic distances to point p0, the level sets of T(x) are the regions of equal weighted geodesic distance to p0, and weighted geodesic paths are orthogonal to level sets of T(x) … the weighted geodesic path of interest is calculated constructing a path from p1 oriented as ∇T(x) in every point … and then obtaining C(s) which minimizes the energy Ecenterline in Equation 5.6 by arc length parameterization … With this approach, centerlines satisfying a criterion of minimal energy and lying on medial axis are computed.”).
Antiga teaches obtaining at least one blood vessel path line by connecting a line extending from the starting point to the ending point according to a searching sequence. (Antiga disclosed in page 40-41: “Once intersection profiles are reconstructed, they can be counted. If one new profile is generated, the surface between the defining and the new profile is a topological cylinder, therefore the new profile is taken as defining profile, and a new step is performed. If no profiles are generated, a dead end of a vessel segment has been found, so the set of probing sphere centers are stored as a vessel segment and the analysis continues with a new segment from an available (i.e. not visited) profile. … It can also happen that during point visiting procedure an available profile is encountered. This means that the current segment ends on a bifurcation which has been already identified, or on an outlet of the model. Each time a bifurcation is encountered, it is assigned a unique id, and its profiles are marked with it. This way, whenever a segment has been constructed, its endpoints are associated with the id of the bifurcations enclosing it. Therefore vascular network topology can be reconstructed without the need of any particular order in visiting segments. During the analysis of segments, an estimate of mean radius is calculated at each step of the probing sphere by computing the mean distance of the points visited at that step from the line defined by the barycenter of the defining and the intersection profiles, which approximates vessel centerline. For bifurcations, the barycenter of the bifurcation surface is calculated, and it is joined to the endpoints of the afferent branches.”).
Regarding claim 13, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 12, wherein a manner for selecting one blood vessel path line as the blood vessel centerline comprises: summing a time taken for each path line of the blood vessel extending from the starting point to the ending point if there are two or more path lines of the blood vessel; (Antiga disclosed in page 108-109: “Source faces are meshed using simple mapping for quadrilateral side face of the triangular based prism on each branch endcap, and tri-primitive scheme for the rest of the source faces. Tri-primitive scheme is a simple scheme which allows to discretize a triangular patch into quadrilaterals (see Figure 6.2). Note how the composition of four disk-quarters and one rectangle on each branch source made following edge node count relations in Equation 6.1 yields a globally symmetric node distribution with respect to two orthogonal axes. The sweeping algorithm used for subsequent volume meshing is the Cooper algorithm. This algorithm begins by first projecting the edge discretization of the source face onto the opposite endcap on the basis of side surface parameterization. … In our case, the side surface of the generalized cylinder is mapped onto a reference rectangle for which one parameter coordinate is periodic. A cut can be induced in the side surface of the generalized cylinder based on surface parameterization such that it is mapped onto the reference rectangle whose parameter coordinate are (s, t), … transfinite interpolation in point x is expressed by the boolean sum … The simplest blending functions satisfying the above conditions for the side surface of a generalized cylinder … where the blending functions for s are periodic.”).
Antiga teaches selecting the path line of the blood vessel with a shortest time as the blood vessel centerline. (Antiga disclosed in page 79-80: “minimization Ecenterline in Equation 5.6 can be also achieved by computing the shortest path on the Voronoi diagram domain between p0 and p1 according to the metric induced by F(x) (setting F(x)=1 yields classic geodesics computed on surface metric). With this approach it is possible to directly extract the global minimum of Ecenterline. In the weighted geodesic approach, once a scalar field is defined on the domain, the aim is to find the path from p0 to p1 for which the integral of the scalar field along the path is minimal (for this reason the path is also called minimal cost or minimal action path). One way to solve this problem is that of defining the weighted geodesic distance of each point of the domain to point p0, and then to trace the path back from p1 to p0 along the gradient of weighted geodesic distance field … Since the scalar field T(x) represents weighted geodesic distances to point p0, the level sets of T(x) are the regions of equal weighted geodesic distance to p0, and weighted geodesic paths are orthogonal to level sets of T(x) … the weighted geodesic path of interest is calculated constructing a path from p1 oriented as ∇T(x) in every point … and then obtaining C(s) which minimizes the energy Ecenterline in Equation 5.6 by arc length parameterization … With this approach, centerlines satisfying a criterion of minimal energy and lying on medial axis are computed.”).
Regarding claim 17, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 6, wherein a manner for acquiring the stenotic section and the stenotic point comprises: simulating and generating a smooth curve of a normal blood vessel according to a set extension trend of the normal blood vessel, as well as the real-time diameter Dt of the blood vessel, the length L of the centerline of the straightened blood vessel; (Antiga disclosed in page 33 section 2.7: “The reconstruction algorithm has been validated on synthetic images of cylinders with different resolutions, … Synthetic cylinders were constructed in such a way to mimic contrast medium in medical images, which decreases smoothly and rapidly near the vessel wall. To this extent, a translated sigmoid function with cylindrical symmetry was constructed, such that its zero level-set was located over sigmoid inflection curve, which corresponds to gradient modulus maxima. … where R is the radius of the cylinder, that is the distance between the symmetry axis and the zero level set of F(r), a controls the steepness of the sigmoid at the inflection point (the gradient modulus at the inflection point is a), and C is a scale factor. Figure 2.15 shows a plot of function F(r) ... In Table 2.2 level sets performance is tested against image noise. Noise was generated by filtering with a Gaussian smoothing filter, of standard deviation equal to 2 pixels, an uniform probability image.” It has been discussed in page vii (last para) that the aim of presenting new tools developed for three-dimensional model reconstruction, geometric analysis, mesh generation and CFD calculation applied to large arteries. Computational geometry techniques have been developed and used to solve specific problems such as segmentation, reconstruction, editing, measurement and discretization of three-dimensional patient-specific models of vasculature).
Antiga teaches comparing the smooth curve of the normal blood vessel generated by simulation with a smooth curve formed by length L-diameter Dt of a patient's actual centerline of the straightened blood vessel to acquire a stenotic lesion section; (Antiga disclosed in page 26 section 2.5.5: “Level sets can be successfully applied to blood vessel 3D modeling by performing the initialization inside the vessels of interest on angiographic images. Under the influence of the inflation term of Equation 2.22, single points turn into sphere-like shapes which eventually merge with their neighbors. Surfaces during evolution, as well as final model surface, can be extracted by contouring the 0 level set of F(x, t) using Marching Cubes algorithm, as shown in Figure 2.11 superimposed to a surface obtained by contouring with user-defined threshold. …”. It has been discussed in page 35 Table 2.2 that Level sets validation results on sigmoidal cylinders sampled at different resolutions (h/R is voxel side size relative to cylinder radius) and with different noise levels (uniform noise was generated and then filtered with a Gaussian smoothing filter with σ 2pixels, in order to select a scale similar to that of real angiographic images. The obtained image was then added to the cylinder function image. Mean, standard deviation and maximum error are expressed in percentage as the difference between distances of model points to cylinder axis and cylinder radius with respect to cylinder radius.” Further, in page 31 Fig. 2.13 disclosed Level sets evolution inside a carotid bifurcation acquired by contrast enhanced CT. Initialization in single vessels based on centerline and bifurcation identification (A). B, C, D: common carotid artery reconstruction. F: highly stenotic internal carotid artery reconstruction. G: final merging of the three reconstructed branches. Lower right: plots of 0-level set over the source images for the corresponding branches.”).
Antiga teaches in the stenotic lesion section, picking a point A with the minimum diameter of the smooth curve formed by the length L-diameter Dt of the patient's actual centerline, and making the point A with the minimum diameter as a stenotic point of the blood vessel segment. (Antiga disclosed in page 107 Figure 6.1: “Automatic decomposition of a carotid bifurcation model based on approximate centerlines computed with the algorithm; the stenotic region is automatically identified and isolated for subsequent adequate meshing.” In page 108-109: “The sweeping algorithm used for subsequent volume meshing is the Cooper algorithm. This algorithm begins by first projecting the edge discretization of the source face onto the opposite endcap on the basis of side surface parameterization. … Transfinite interpolation is a fast technique to map the points of a reference domain onto a physical domain once the description of its boundary is given. In our case, the side surface of the generalized cylinder is mapped onto a reference rectangle … A cut can be induced in the side surface of the generalized cylinder based on surface parameterization such that it is mapped onto the reference rectangle whose parameter coordinate are (s, t), … transfinite interpolation in point x is expressed by the boolean sum …”. Further, in page 109-111: “The last step of mesh generation is the creation of internal nodes and elements, which is the core of the Cooper algorithm. … From our experience, the algorithm results to be very effective in preserving cross-sectional node distribution even in regions of high stenosis grade, as shown in Figure 6.3. Boundary layer elements maintain the same aspect ratio with respect to the rest of cross-sectional elements, which is a great advantage of using the Cooper algorithm in this context. Therefore, the meshes generated by the described approach meet the requirements of being well-aligned with the expected direction of flow and presenting scale-dependent boundary layers. The resulting volume elements are linear hexahedra of high quality. Figure 6.4 shows the final hexahedral mesh for the stenotic carotid bifurcation …”).
Regarding claim 18, Antiga teaches a device for synthesizing a mathematical model of a blood vessel, used for the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 1, is incorporating the rejections of claim 1, because claim 18 has substantially similar claim language as claim 1, therefore claim 18 is rejected under 35 U.S.C. 102(a)(1) as being anticipated by Antiga as discussed above for substantially similar rationale.
The additional elements of claim 18: “a three-dimensional blood vessel model structure, a single-layer mesh model structure and a blood vessel mathematical model structure” are being taught by Antiga (in page 4, it has been disclosed “patient-specific vascular model reconstruction techniques rely on a set of techniques which imply low-level operator interaction, such as identification of vessel lumen on 2D images, reconstruction of the 3D model from the stack of 2D sections by means of CAD software, editing of the model, discretization of the volume into small elements for CFD”). In light of Specification of current Application, Applicant stated in para [00191 and 00192]: “The present disclosure provides a computer storage medium having stored thereon a computer program to be executed by a processor, and the aforementioned method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis is implemented when the computer program is executed by the processor. A person skilled in the art knows that various aspects of the present disclosure can be implemented as a system, a method, or a computer program product. Therefore, each aspect of the present disclosure can be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation …”. Therefore, a person skilled in the art would understand that any software or computer program can perform/implement the abovementioned model structures (e.g., three-dimensional blood vessel model structure, a single-layer mesh model structure and a blood vessel mathematical model structure). Accordingly, Antiga teaches the whole claim limitations of claim 18.
Regarding claim 20, Antiga teaches a computer storage medium having stored thereon a computer program to be executed by a processor, wherein the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 1 is implemented when the computer program is executed by the processor. (Antiga disclosed in page 4: “patient-specific vascular model reconstruction techniques rely on a set of techniques which imply low-level operator interaction, such as identification of vessel lumen on 2D images, reconstruction of the 3D model from the stack of 2D sections by means of CAD software, editing of the model, discretization of the volume into small elements for CFD”. Therefore, a person skilled in the art would understand that any computer storage medium (memory) having a computer program (or software) stored in a computer system, which is executed by a processor. Accordingly, Antiga teaches the computer program/software to perform the abovementioned claimed invention).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham, v. John Deere Co., 383 U.S.1.148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
12.1 Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Antiga and in view of a conference paper “Meshing strategy for bifurcation arteries in the context of blood flow simulation accuracy” by Natalia Lewandowska et al. (hereinafter Lewandowska, conference paper published on 2019).
Regarding claim 4, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 2, However, Antiga doesn’t explicitly teach the limitation “the triangle that uses as the smallest unit is an isosceles triangle.”
wherein Lewandowska teaches the triangle that uses as the smallest unit is an isosceles triangle. (Under BRI and according to conventional meaning in the art, Examiner would construe the claim element “isosceles triangle” as “equilibrium triangle”.
Lewandowska disclosed in page 1 heading ‘Abstract’: “The study presents a mesh dependency study for a carotid artery bifurcation geometry of a real-life specimen. … Apart from numerical results, overall mesh creation worktime, overall analysis stability are compared with the mesh quality results: cell non-orthogonality, cell skew and aspect ratio.” In page 2-3 section 4.2: “Following mesh quality metrics are used to assess the mesh quality: orthogonal quality, skew and maximum aspect ratio. … For a hexahedral element, skewness is defined as the normalized worst angle between each of the 6 face normal vectors … For tri elements, skewness is defined as the ratio between the area of the element and the area of an equilateral triangle having the same circumcircle.”
The disclosure above “mesh quality metrics are used to assess the mesh quality: skew”; further, for tri elements, skewness is defined such as the “the area of an equilateral triangle having the same circumcircle” correspond to claim limitation “performing meshing using a triangle as the smallest unit is an isosceles triangle”).
Therefore, Antiga and Lewandowska are analogous art because they are related in generating mesh for a carotid artery bifurcation geometry. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Antiga and Lewandowska, to modify performing meshing using triangle as the unit on a circumferential surface of the 3D blood vessel model of Antiga, to include the teaching of Lewandowska in order to perform meshing using a triangle as an isosceles/equilateral triangle and the results would have been predictable to one of ordinary skill in the art (See MPEP 2143(I)(B), Examples 1-11). The suggestion/motivation for doing so would have been obvious by Lewandowska because “Based on the conducted research, it can be noted that while choosing the type of computational grid for modelling blood flow in the arteries, the key flow parameters to be analyzed should be taken into account. In the case of flow analysis in the context of aneurysm formation, WSS are mainly analyzed. In this case, much more accurate results can be obtained by using structural, hexagonal meshes, it is recommended to perform a fully structural mesh with the value of y+ equal to1. The implementation of good quality mesh, especially for such irregular geometries as the carotid artery, is time-consuming and the final grid has the most elements, but calculations made on such a mesh gives the most accurate results both in terms of WSS and flow patterns.” (Lewandowska disclosed in page 6 heading ‘Conclusion’). Therefore, it would have been obvious to combine Lewandowska with Antiga to obtain the invention as specified in the instant claim(s).
12.2 Claims 14 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Antiga and in view of an NPL paper “A Review of Vessel Extraction Techniques and Algorithms” by Cemil Kirbas et al. (hereinafter Kirbas, NPL published on 2004).
Regarding claim 14, Antiga teaches the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 7, wherein a manner for extracting a blood vessel centerline from the two-dimensional coronary artery angiogram image of each body position along a direction from an inlet of the coronary artery to an end of the coronary artery comprises: performing image processing for the blood vessel partial area image to acquire an rough trend line of the blood vessel between the starting point and the ending point; (Antiga disclosed in page 87-88 section 5.3.3: “The resulting centerline is a piecewise linear line defined on the Voronoi diagram, whose vertices lie on Voronoi polygon boundaries. Values of Voronoi sphere radius R(x) are therefore defined on centerlines, so that centerline points are associated with maximal inscribed spheres, as shown in Figure 5.10. Since centerlines were constructed to lie on local maxima of distance from the boundary, there is a tight connection between maximal sphere radius and minimum projection diameter used in clinical evaluation. In fact, classic angiographic vessel diameter evaluation is performed considering the minimum diameter obtained by measurements on different projections. … our method provides the measure of the minimum vessel diameter with respect to the projection angle, as shown in Figure 5.11, plotted against centerline abscissa in Figure 5.12. The availability of a robust method for centerline computation and diameter measurement as the one presented here allows to characterize blood vessel geometry in a synthetic way, …”).
Antiga teaches acquiring a rough edge line of the blood vessel, (Antiga disclosed in page 86 headline ‘Backtracing’ (last para): “consider Voronoi polygons sharing the edge on which ˜x is defined. The point on polygon edges which yields the maximum descent of T(x) from ˜x is set to be the new centerline point. Since the polygon is convex, the centerline is ensured to lay on the Voronoi diagram. If the distance of the maximum descent point to a Voronoi vertex is lower than a given threshold, the new centerline point is set to coincide with the Voronoi vertex. This last adjustment is important, because if a point is near to a vertex but still results to lie on an incident edge, only the polygons sharing the edge are taken into account as neighbor polygons, …”).
However, Antiga doesn’t explicitly teach the limitation “an image between the rough edge lines of the blood vessel comprising the rough trend line of the blood vessel is a blood vessel skeleton; extracting the blood vessel centerline from the blood vessel skeleton.”
wherein Kirbas teaches an image between the rough edge lines of the blood vessel comprising the rough trend line of the blood vessel is a blood vessel skeleton; (Kirbas disclosed in page 87 section 3.4: “vessel tree structures from MRA images using a gray-scale skeletonizing method based on the ordered region-growing algorithm that represents the image as an acyclic graph using the image voxels connectivity. … After forming the acyclic graph, a skeletonizing process is applied to extract the tree in two different methods. In the first method, user explicitly selects the origin, which serves as the seed point of the graph, of the tree and endpoints of the vessels. Then, vessel segments are extracted by tracing the path from each endpoint to the origin of the graph.
Kirbas teaches extracting the blood vessel centerline from the blood vessel skeleton. (Kirbas disclosed in page 82 section 3.2 (left col.): “Skeleton-based methods extract blood vessel centerlines. The vessel tree is created by connecting these centerlines. Different approaches are used to extract the centerline structure. … The resulting centerline structure is used for 3D reconstruction. … Finally, a 3D thinning algorithm is applied to extract the vessel centerlines. The resulting centerline structure is used to analyze and classify the blood vessels.”).
Therefore, Antiga and Kirbas are analogous art because they are related in performing image processing for a carotid artery or the blood vessel. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Antiga and Kirbas, to modify acquiring a rough edge line of the blood vessel while performing image processing of Antiga, to include Kirbas teaching in order to extract blood vessel centerlines by using Skeleton-based methods and the results would have been predictable to one of ordinary skill in the art (See MPEP 2143(I)(B), Examples 1-11). The suggestion/motivation for doing so would have been obvious by Kirbas because “We present a survey of vessel extraction techniques and algorithms. We put the various vessel extraction approaches and techniques in perspective by means of a classification of the existing research. While we have mainly targeted the extraction of blood vessels, neurosvascular structure in particular, we have also reviewed some of the segmentation methods for the tubular objects that show similar characteristics to vessels. We have divided vessel segmentation algorithms and techniques into six main categories: (1) pattern recognition techniques, (2) model-based approaches, (3) tracking-based approaches, (4) artificial intelligence-based approaches, (5) neural network-based approaches, and (6) tube-like object detection approaches.” (Kirbas disclosed in page 81 heading ‘Abstract’). Therefore, it would have been obvious to combine Kirbas with Antiga to obtain the invention as specified in the instant claim(s).
Regarding claim 19, Antiga teaches a device for synthesizing a mathematical model of a blood vessel according to claim 18 (as discussed above).
Kirbas teaches a coronary artery analysis system (Kirbas disclosed in page 83 section 3.1 (right col. 2nd and 3rd para): “Sarwal and Dhawan reconstruct 3D coronary arteries from three views by matching branch points in each view. Their method is based on simplex method-based linear programming and relaxation-based consistent labeling. … The extracted vessel tree is used for 3D reconstruction. Chwialkowski et al. employ multiresolution analysis based on wavelet transform. Their work aims at automated qualitative analysis of arterial flow using velocity-sensitive, phase contrast MR images. The segmentation process is applied to the magnitude image and the velocity information from the phase difference image is integrated on the resulting vessel area to get the blood flow measurement.”).
12.3 Claims 15 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Antiga and in view of Kirbas and further in view of an NPL paper “A 3D Model of Human Cerebrovasculature Derived from 3T Magnetic Resonance Angiography Wieslaw L. Nowinski et al. (hereinafter Nowinski, NPL published on 2009).
Regarding claim 15, Antiga and Kirbas teach the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 14, wherein a manner for extracting a blood vessel centerline from the blood vessel skeleton comprises: Antiga teaches performing meshing for the blood vessel partial area image after image processing; (Antiga disclosed in page 109-111: “The last step of mesh generation is the creation of internal nodes and elements, which is the core of the Cooper algorithm. Being a proprietary algorithm, the exact procedure is not well documented. The author refers to the method used as to a “least square weighted residual method which maintains the overall shape and quality of the mesh even for drastic distortion of the geometry”. From our experience, the algorithm results to be very effective in preserving cross-sectional node distribution even in regions of high stenosis grade, as shown in Figure 6.3. … Therefore, the meshes generated by the described approach meet the requirements of being well-aligned with the expected direction of flow and presenting scale-dependent boundary layers. The resulting volume elements are linear hexahedra of high quality. Figure 6.4 shows the final hexahedral mesh for the stenotic carotid bifurcation considered in this section …”. It has been discussed in page 103 section 6.1 that the problem of accurately reconstructing 3D models of vascular segments from volumetric angiographic images was solved in previous chapter).
Kirbas teaches obtaining at least one connection line from the starting point to the ending point according to a searching sequence; (Kirbas disclosed in page 106 (right col.): “method of tracing the coronary arterial boundaries with sub-branches from XRAs. … Tracing contours sequentially. Edge points are evaluated and fixed by employing a smoothing differential operator on the scan line perpendicular to the direction of the vessel. … Sequential contour tracing achieved by incorporating the features, such as the central point, the searching direction, and the search range, detected from previous step into the next step.” Further, in page 108: “The tracking algorithm is an adaptive iterating procedure and models the vessel profile using Gaussian function. The algorithm also utilizes spatial continuity properties of the vessel segments to improve computational performance in regions where the vessel segments are relatively straight. This method requires the user to identify beginning and ending search points and first vessel direction manually.
Kirbas teaches selecting one connection line as the blood vessel centerline if there are two or more connection lines. (Kirbas disclosed in page 86-87: “automatically segment coronary vessels in angiograms based on temporal, spatial, and structural constraints. The algorithm starts with a low pass filtering applied to the image as preprocessing. Then, initial segmentation starts with a user-supplied seed point. The system starts a region growing process to extract the initial approximation to the vessel structure. After that, the centerlines are extracted by employing a balloon test. Next, undetected vessel segments are located by a spatial expansion algorithm. … This information is extracted by applying an acceptance and rejection test using graph theory. Figure 3 shows the result of their method applied to an angiogram image. Due to the extraction of the centerlines, this work can also be classified as a skeleton-based approach …”).
However, Antiga and Kirbas do not explicitly teach the limitation “along a direction from the starting point to the ending point, according to a RGB value, searching the blood vessel skeleton for a point having a minimum difference in RGB value with the starting point from intersecting points of surrounding m meshes as a second point, searching for a point having a minimum difference in RGB value with the second point from intersecting points of surrounding m meshes as a third point, and repeating the above step for the third point until reaching the ending point, where m is a positive integer greater than or equal to 1;”
Nowinski teaches along a direction from the starting point to the ending point, according to a RGB value, searching the blood vessel skeleton for a point having a minimum difference in RGB value with the starting point from intersecting points of surrounding m meshes as a second point, searching for a point having a minimum difference in RGB value with the second point from intersecting points of surrounding m meshes as a third point, and repeating the above step for the third point until reaching the ending point, where m is a positive integer greater than or equal to 1; (Nowinski disclosed in page 26-28: “By connecting the consecutive circles or ellipses, we get the vascular frame of a vessel. This frame is represented as a set of triangles. … To build the bifurcation surface, the method of Catmull and Clark of recursively generated B-spline surfaces is used. … By using the control points of this frame we build a bicubic uniform B-spline surface … This frame has undergone two B-subdivision iterations. Every subdivision re-parametrizes the surface by substitution of variables … generating a new mesh with a greater number of patches. … The vascular model was uniquely colored manually, such that each labeled segment has its own color. The veins were colored in blue and the arteries were colored by applying the split complementary color scheme to blue. The resulting colors represented in RGB painted the main vascular groups. Within each group, two of the RGB colors were kept constant while the third color was changing distally.”).
Therefore, Antiga, Kirbas and Nowinski are analogous art because they are related in generating mesh for a carotid artery bifurcation geometry. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Antiga, Kirbas and Nowinski, to modify performing meshing for the blood vessel partial area image after image processing of Antiga, to include the teaching of Nowinski to search the blood vessel with minimum RGB value in a surrounding mesh for the blood vessel and the results would have been predictable to one of ordinary skill in the art (See MPEP 2143(I)(B), Examples 1-11). The suggestion/motivation for doing so would have been obvious by Nowinski because “Our approach replaces the tedious and time consuming process of checking and correcting automatic segmentation results done at 2D image level with an aggregate and faster process at 3D model level. The creation of the vascular model required vessel pre-segmentation, centerline extraction, vascular segments connection, centerline smoothing, vessel surface construction, vessel grouping, tracking, editing, labeling, setting diameter, and checking correctness and completeness. The speedup of our approach (the number of 2D segmented areas/the number of 3D vascular segments) is 34. This cerebrovascular model can serve as a reference framework in clinical, research, and educational applications.” (Nowinski disclosed in page 23 heading ‘Abstract’). Therefore, it would have been obvious to combine Nowinski with Antiga and Kirbas to obtain the invention as specified in the instant claim(s).
Regarding claim 16, Antiga, Kirbas and Nowinski teach the method for synthesizing a mathematical model of a blood vessel having a stenotic lesion section for fluid dynamics analysis according to claim 15, wherein Antiga teaches a manner for obtaining a straightened blood vessel contour line according to the straightened blood vessel centerline and the image of the straightened blood vessel comprises: setting a threshold Dthreshold for a diameter of the blood vessel on the image of the straightened blood vessel; (Antiga disclosed in page 26 section 2.5.5: “Level sets can be successfully applied to blood vessel 3D modeling by performing the initialization inside the vessels of interest on angiographic images. Under the influence of the inflation term of Equation 2.22, single points turn into sphere-like shapes which eventually merge with their neighbors. Surfaces during evolution, as well as final model surface, can be extracted by contouring the 0 level set of F(x,t) using Marching Cubes algorithm, as shown in Figure 2.11 superimposed to a surface obtained by contouring with user-defined threshold.”).
Antiga teaches generating a preset contour line of the blood vessel on both sides of a centerline of the straightened blood vessel according to the Dthreshold; (Antiga disclosed in page 30 section 2.5.5: “since evolution parameters are dependent on vessel scale, we let level sets evolve into single vessels, or into groups of vessels of similar scale … we then merge the Fi(x) functions resulting from N single vessel evolutions, and finally extract model surface by contouring the merged Fm(x) function with Marching Cubes algorithm. Since in the sparse-field approach level sets represent the signed distance function from the 0 level set, with negative values inside the model and positive values on the rest of the domain, merging of N level sets scalar fields is performed selecting their minimum value … An example of single vessel evolution and merging for a carotid bifurcation is depicted in Figure 2.13, while the intersections of model points with gradient magnitude images in the region of the bifurcation apex are shown in Figure 2.14.”).
Antiga teaches making the preset contour line of the blood vessel step-by-step approach the center line of the straightened blood vessel to acquire a straightened blood vessel contour line. (Antiga disclosed in page 45-46 section 3.5.2: “automatic detection of vessel topology and quick retrival of vessel centerline approximations can result to be very useful. … We used the following approach for initialization of level sets, … First the volume of interest is contoured with Marching Cubes at a user-specified threshold near the maximum transition between contrast medium and the surrounding tissue. The contouring surface is then near to the vascular wall and reproduces the topology of the vascular tract. The application of the topological analysis algorithm presented in this chapter to the contouring surface yields an approximation of interconnecting centerlines. Level sets initialization is then performed by interactively selecting single centerlines, and making the deformable model start to evolve from centerline points. … This way it is possible to separately initialize and control the evolution of level sets inside vessels of the same size, thus avoiding scale-dependence effects on evolution parameters, …”).
Conclusion
13. The prior arts made of record and not relied upon is considered pertinent to applicant's disclosure. An NPL “Comprehensive Modeling and Visualization of Cardiac Anatomy and Physiology from CT Imaging and Computer Simulations” by Guanglei Xiong et al. disclosed framework allows for visualizing the patientspecific simulation of coronary hemodynamics by applying CFD to CT angiography images. The simulated coronary blood velocity, and pressure, as well as shear stress and total traction forces on the vessel wall was displayed with both the anatomic context of segmented heart models and the physiologic context of myocardial perfusion. The goal of this framework is to provide computer-aided diagnosis with automated modeling and integrated visualization for anatomic (i.e., heart and coronary arteries), functional (i.e., cardiac motion), and physiologic information (i.e., myocardial perfusion and coronary hemodynamics) that is clinically relevant, which may extend and improve their current work flow over unassisted procedures. The hybrid approach in this framework is not only capable of capturing complex vascular geometry with asymmetric or noncircular cross sections but is also able to support queries for each individual vessel and the connecting branches.
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/NUPUR DEBNATH/Examiner, Art Unit 2186
/RENEE D CHAVEZ/Supervisory Patent Examiner, Art Unit 2186