DETAILED ACTION
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
Figures 1 and 5 is objected to as depicting a block diagram without “readily identifiable” descriptors of each block, as required by 37 CFR 1.84(n). Rule 84(n) requires “labeled representations” of graphical symbols, such as blocks; and any that are “not universally recognized may be used, subject to approval by the Office, if they are not likely to be confused with existing conventional symbols, and if they are readily identifiable.” In the case of figures 1 and 5, the blocks are not readily identifiable per se and therefore require the insertion of text that identifies the function of that block. That is, each vacant block should be provided with a corresponding label identifying its function or purpose.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “determination unit”, “reconstruction subunit”, “backprojection subunit”, “computing unit”, and “distribution unit” in claim 14. Such claim limitation(s) is/are: “first training interface”, “second training interface”, “third training interface”, and “training computing unit” in claim 15.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
Claim(s) 1-6 and 14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 2018/0199905 A1 (Kowarschik).
As per claim 1, Kowarschik teaches a method for reducing artifacts occurring due to vessel overlaps in a four- dimensional angiography dataset, acquired with administration of a contrast agent, of an acquisition region of interest of a blood circulatory system of a patient, wherein a three- dimensional vessel dataset of the blood circulatory system is reconstructed from two- dimensional digital subtraction angiography projection images showing the blood circulatory system and having been acquired at respective time points in a specific time interval, and wherein the four-dimensional angiography dataset is determined by backprojection of the two-dimensional digital subtraction angiography projection images into the three-dimensional vessel dataset (Kowarschik:
Abstract: “Vessel overlap artifacts are reduced in a four-dimensional angiography data set a blood vessel system of a patient with a contrast medium. A three-dimensional vessel data set of the blood vessel system is reconstructed from two-dimensional projection images of digital subtraction angiography showing the blood vessel system, determined by multiplicative back projection of the projection images into the vessel data set or a base data set of the four-dimensional angiography data set derived vessel data set. A plausibility check is performed with vessel sections displayed as filled with contrast medium in partial image data sets of the angiography data set assigned to all individual, and different instants of the covered period are checked against a plausibility check criterion checking for a contrast medium-filled connection to an admissible source point, after which a corrected partial image data set is determined containing only vessel sections satisfying the plausibility check criterion.”
Para 4: “Therefore, an algorithm of this kind may create artifacts due to vessel overlapping in that particular vessel segments, displayed too early or too late as being filled with contrast medium. For the user (e.g., a doctor making a diagnosis), the image quality and the clinical significance of this four-dimensional are adversely affected.”;
Para 5: “To reduce the number of overlap artifacts, it has already been proposed, during multiplicative back projection for determining the three-dimensional partial image data sets assigned to different instants, to simultaneously determine a likewise four-dimensional confidence map as a confidence data set describing the vessel overlap along relevant, used beams. The confidence value 0 is conventionally assigned to a strong vessel overlap and a confidence value 1 is conventionally assigned to a non-existent vessel overlap. Confidence values of the confidence data set may be determined by “counting” the vessels (e.g., by integration along the beam and comparison with at least one threshold value). Based on the four-dimensional confidence data set describing the vessel overlap, it is possible to interpolate unreliable intensity values of the provisional four-dimensional angiography image data set between sufficiently reliable neighboring values in the time and therefore replace the less reliable values (e.g., those falling below a threshold value for the confidence value).”;
Para 8: “reducing vessel overlap artifacts, because of the overlap of vessels, is improved.”;
Para 9: “reducing vessel overlap artifacts that occur in a four-dimensional angiography data set of a recording region of interest of a blood vessel system of a patient recorded with administration of a contrast medium. A three-dimensional vessel data set of the blood vessel system is reconstructed from two-dimensional projection images of the digital subtraction angiography showing the blood vessel system, determined by multiplicative back projection of the projection images into the vessel data set or a base data set of the four-dimensional angiography data set derived therefrom”;
Para 11: “The four-dimensional angiography data set covers a particular period of the course of the contrast medium concentration in the recording region by way of a time series of three-dimensional partial image data sets. For example, not just one three-dimensional position (voxel) corresponds to each image element of the four-dimensional angiography data set, instead, over the period, each of the image elements includes a contrast medium characteristic curve such that partial image data sets describing contrast medium states corresponding to various instants within the period result from the four-dimensional angiography data set. An instant is a section of the period. For example, an instant, depending on the temporal resolution of the four-dimensional angiography data set, conventionally covers a certain time interval corresponding to the smallest resolvable unit of time or a multiple thereof.”;
Para 41: “The angiography data set 4 is ultimately determined as a series of three-dimensional partial image data sets assigned to different instants within the covered period”;
: reducing vessel overlap artifacts in 4D angiography), the method comprising:
generating distribution data relating to a concentration of the contrast agent in the blood circulatory system at the respective time points for (note that only one of the following alternatives is required) the three-dimensional vessel dataset or for a reduced dataset derived therefrom (Kowarschik:
para 38: “the projection images relating to the respective instants of the period (e.g., covered by the series of projection images 1)”;
para 41: “a temporal contrast medium characteristic curve results for these voxels”;
generating contrast agent progression for 3D vessel data set or reduced dataset (i.e. vessel centerline)); and
distributing a color intensity of a pixel of a respective two-dimensional digital subtraction angiography projection image of the two-dimensional digital subtraction angiography projection images, wherein the pixel shows a contrast agent filling state according to the distribution data at a respective time point of the two-dimensional digital subtraction angiography projection image across voxels of the three-dimensional vessel dataset that lie along a ray associated with the pixel in the backprojection (Kowarschik:
para 5 (referenced above);
para 27: “determining a four-dimensional angiography data set, recorded with the administration of contrast medium, of a recording region of interest of a blood vessel system of a patient, having a reconstruction sub-unit for reconstruction of a three-dimensional vessel data set of the blood vessel system from two-dimensional projection images from digital subtraction angiography, showing the blood vessel system, and a back projection sub-unit for determining the angiography data set by multiplicative back projection of the projection images into the vessel data set or a base data set derived therefrom. The device also includes a plausibility check unit for checking vessel sections displayed as filled with contrast medium by way of a plausibility check criterion that checks for the existence of a contrast medium-filled connection to an admissible source point in partial image data sets of the angiography data set assigned to all individual, different instants of the covered period”;
para 38: “Thus, a check is made as to which blood vessels are located along a beam leading to a pixel of the projection image 1 currently being considered. Contrast medium filling of the pixel is then ultimately distributed among the vessel voxels of the vessel data set 3 located on the beam. The multiplication highlights vessel voxels of pixels of the projection image 1 that display contrast medium filling and suppresses vessel voxels pixels without contrast medium filling.”;
para 41: “The correction performed in interpolation act 6 is provided such that, due to the directions of projection, which change over time, during recording of the projection images 1, an overlap, and therefore a low reliability, is depicted by a low confidence value, which exists only over certain periods. If less reliable values in successive partial image data sets of the angiography data set 4 are replaced by interpolated values determined by interpolation between reliable, temporally neighboring values in the angiography data set, corresponding contrast medium filling results with a consistent contrast medium curve over time, whereas with reliable values of zero as neighboring values, erroneous contrast medium fillings are removed by the temporal interpolation.”;
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See arguments and citations offered in rejecting claim 2 below;
perform (e.g. multiplicative) backprojection according to generated contrast agent progression for respective timepoints).
As per claim 2, Kowarschik teaches the method as claimed in claim 1, further comprising:
determining a number of voxels lying on the ray from the three-dimensional vessel dataset; and
assigning a measure for the determined number to the voxels, wherein the color intensity of the pixel is distributed according to the distribution data when the measure falls below a predefined value (Kowarschik: See arguments and citations offered in rejecting claim 1 above;
Abstract: “Vessel overlap artifacts are reduced in a four-dimensional angiography data set a blood vessel system of a patient with a contrast medium. A three-dimensional vessel data set of the blood vessel system is reconstructed from two-dimensional projection images of digital subtraction angiography showing the blood vessel system, determined by multiplicative back projection of the projection images into the vessel data set or a base data set of the four-dimensional angiography data set derived vessel data set. A plausibility check is performed with vessel sections displayed as filled with contrast medium in partial image data sets of the angiography data set assigned to all individual, and different instants of the covered period are checked against a plausibility check criterion checking for a contrast medium-filled connection to an admissible source point, after which a corrected partial image data set is determined containing only vessel sections satisfying the plausibility check criterion.”;
Para 5: “To reduce the number of overlap artifacts, it has already been proposed, during multiplicative back projection for determining the three-dimensional partial image data sets assigned to different instants, to simultaneously determine a likewise four-dimensional confidence map as a confidence data set describing the vessel overlap along relevant, used beams. The confidence value 0 is conventionally assigned to a strong vessel overlap and a confidence value 1 is conventionally assigned to a non-existent vessel overlap. Confidence values of the confidence data set may be determined by “counting” the vessels (e.g., by integration along the beam and comparison with at least one threshold value). Based on the four-dimensional confidence data set describing the vessel overlap, it is possible to interpolate unreliable intensity values of the provisional four-dimensional angiography image data set between sufficiently reliable neighboring values in the time and therefore replace the less reliable values (e.g., those falling below a threshold value for the confidence value).”;
Para 10: “plausibility check act, vessel sections displayed as filled with contrast medium in partial image data sets of the angiography data set assigned to all individual, different instants of the covered period are checked against a plausibility check criterion checking for the existence of a contrast medium-filled connection to an admissible source point. A corrected partial image data set is determined containing only vessel sections that satisfy the plausibility check criterion.”;
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Para 40 (shown below): “For each voxel and each instant, the confidence data set 7 contains a confidence value as a measure of the reliability of the corresponding angiography data value of the provisional angiography data set 4. To determine the confidence value, a check is performed to determine how many vessel voxels and/or vessels are located along a beam during multiplicative back projection, such that the confidence value ultimately indicates a probability that different blood vessels are located along this beam 2. The confidence value is standardized to an interval between 0 and 1. A confidence value of 1 indicates a high degree of certainty that a plurality of blood vessels is located along the beam; a confidence value of 0 indicates a high degree of certainty that a plurality of vessels is located along the beam”;
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: Intensity of the projection is backprojected when then number of voxels along the backprojection direction or ray is below a threshold).
As per claim 3, Kowarschik teaches the method of claim 2, further comprising: determining vessel centerlines of the blood circulatory system as the reduced dataset from the three-dimensional vessel dataset, wherein the distribution data relating to the concentration of the contrast agent in the blood circulatory system is generated for the vessel centerlines (Kowarschik: See arguments and citations offered in rejecting claim 2 above.
note that this claim pertains to the “reduced dataset” alternative of claim 1, which is not required.
Note that claims 3-4 are fairly analogous in recitation to claims 5-6 – except for different dependency.
Contrast agent progression is generated for vessel centerlines).
As per claim 4, Kowarschik teaches the method of claim 3, wherein the distribution data relating to the concentration of the contrast agent for the vessel centerlines is extrapolated onto the three- dimensional vessel dataset (Kowarschik:
See arguments and citations offered in rejecting claim 2 above.
note that this claim pertains to the “reduced dataset” alternative of claim 1, which is not required.
Note that claims 3-4 are fairly analogous in recitation to claims 5-6 – except for different dependency.
Contrast agent progression is extrapolated onto 3D vessel dataset).
As per claim 5, Kowarschik teaches the method of claim 1, further comprising: determining vessel centerlines of the blood circulatory system as the reduced dataset from the three-dimensional vessel dataset, wherein the distribution data relating to the concentration of the contrast agent in the blood circulatory system is generated for the vessel centerlines (Kowarschik: See arguments and citations offered in rejecting claim 2 above.
note that this claim pertains to the “reduced dataset” alternative of claim 1, which is not required.
Note that claims 3-4 are fairly analogous in recitation to claims 5-6 – except for different dependency.
Contrast agent progression is generated for vessel centerlines).
As per claim 6, Kowarschik teaches the method of claim 5, wherein the distribution data relating to the concentration of the contrast agent for the vessel centerlines is extrapolated onto the three- dimensional vessel dataset (Kowarschik: See arguments and citations offered in rejecting claim 2 above.
note that this claim pertains to the “reduced dataset” alternative of claim 1, which is not required.
Note that claims 3-4 are fairly analogous in recitation to claims 5-6 – except for different dependency.
Contrast agent progression is extrapolated onto 3D vessel dataset).
As per claim(s) 14, arguments made in rejecting claim(s) 1 are analogous. Kowarschik also teaches image processing device comprising: a determination unit; a reconstruction subunit; a backprojection subunit; a computing unit; and a distribution unit (Kowarschik: See arguments and citations offered in rejecting claim 2 above; Figs. 6 and 1 and associated text).
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.
Claim(s) 9 is rejected under 35 U.S.C. 103 as being unpatentable over Kowarschik as applied to claim 1 above, and further in view of US 20080020362 A1 (Cotin).
As per claim 9, Kowarschik teaches the method of claim 1. Kowarschik does not teach the distribution data relating to the concentration of the contrast agent is generated as output data of a hemodynamic simulation of a virtual blood flow virtually mixed with the contrast agent in the blood circulatory system reconstructed by the three-dimensional vessel dataset. Cotin teaches these limitations (Cotin:
Abstract: “computing hemodynamics inside the vascular model. One embodiment includes reproducing visual feedback, using synthetic X-ray imaging and/or or visible light rendering. One embodiment includes generating contrast agent injection and propagation through a tubular network”;
Para 33: “simulating the propagation of contrast agent in a vascular model;”
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[0042] Computing accurate hemodynamics inside the vascular model, including the changes induced by the therapy or the procedure [0043] Reproducing visual feedback, either using synthetic X-ray imaging or visible light rendering, with a high level of fidelity [0044] Generating realistic contrast agent injection and propagation through a tubular network;
[0066] FIG. 6 shows an exemplary bifurcation image 180 created using an exemplary embodiment of the inventive reconstruction method. The reconstructed surface 182 is smooth yet uses a minimal number of surface elements to provide efficient rendering and collision detection with medical devices.
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[0048] Various features of the invention embodiments include catheter and guidewire finite element models, real-time one-dimensional fluid dynamics of blood flow, volumetric contrast agent propagation;
Para 108: “volume rendering for simulating images directly from a CT dataset 352”
Para 115: “generates real-time synthetic X-ray images directly from CT/CTA volume datasets”;
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[0122] 1. Unified framework to handle various types of contrast agents: depending on the type of contrast agent, the degree of its diffusion into the blood stream varies. By adjusting the value of diffusion coefficient according to contrast agent type, a particular type of contrast agent can be simulated accurately.
[0127] FIG. 21 shows an exemplary sequence of steps implementing a computation process simulating the propagation of contrast agent in a vascular model. After initialization in step 300, a determination that the simulation is on in step 302, the boundary conditions are set in step 304 and contrast agent concentration is synchronized in step 306, simulation process enters an infinite loop 308 that updates the boundary conditions and synchronizes the concentration value at the branch points.
[0128] FIG. 22 shows the propagation of contrast agent in a vascular model 350 with bifurcation. The color bar 352 at the right indicates the value of the contrast agent concentration from 0 to 1. The simulation of such propagation is determined by FTCS solution of one-dimensional advection-diffusion equation.
[0129] In another aspect of the invention, a real-time algorithm computes contrast agent propagation that updates a volumetric representation of the vascular network. This approach improves greatly the realism of the visual feedback compared to methods based on polygon-based representations. The solution of the advection-diffusion equation gives the concentration value of contrast agent at every sampling point along the medial axis of the vascular network, as shown in FIGS. 23a-c
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[0147] An interventional radiology simulator can include one or more of multi-representation vascular anatomical model, catheters and guidewire models based on wire-like deformable structure, therapeutic device models using real-time tubular deformable representation, include a collision detection/collision response component, blood flow computation associated with contrast agent propagation).
Thus, it would have been obvious for one of ordinary skill in the art, prior to filing, to implement the teachings of Cotin into Kowarschik since both Kowarschik and Cotin suggest a practical solution and field of endeavor of a digital subtract angiographic system for generating contrast agent distribution data in general and Cotin additionally provides teachings that can be incorporated into Kowarschik in that the contrast agent distribution data is generated via simulation so that “The simulator can be optimized for real-time performance on an affordable personal computer platform. This will permit students to learn and err on a computer, so that interventional procedures are safer and faster.” (Cotin: para 48). The teachings of Cotin can be incorporated into Kowarschik in that the contrast agent distribution data is generated via simulation. Furthermore, one of ordinary skill in the art could have combined the elements as claimed by known methods and, in combination, each component functions the same as it does separately. One of ordinary skill in the art would have recognized that the results of the combination would be predictable.
Allowable Subject Matter
Claims 7, 8, 10-13, and 15 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. The following is a statement of reasons for the indication of allowable subject matter: Limitations pertaining to “the trained function is applied to the two-dimensional digital subtraction angiography projection images and the three-dimensional vessel dataset or the reduced dataset as input data”, in conjunction with other limitations present in the independent claims 10 and 15 and dependent claim 7 and its base claim 1, distinguish over the prior art.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Atiba Fitzpatrick whose telephone number is (571) 270-5255. The examiner can normally be reached on M-F 10:00am-6pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Bee can be reached on (571) 270-5183. The fax phone number for Atiba Fitzpatrick is (571) 270-6255.
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Atiba Fitzpatrick
/ATIBA O FITZPATRICK/
Primary Examiner, Art Unit 2677