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 .
Claim Objections
Claims 1, 10-11, and 17 are objected to because of the following informalities:
In claim 1, line 7, the term “determine if the segmented” should be changed to “determine when the segmented” in order to be positively recited.
In claim 10, line 2, the term “wall if a cursor” should be changed to “wall when a cursor” in order to be positively recited.
In claim 11, line 2, the term “wall if a cursor” should be changed to “wall when a cursor” in order to be positively recited.
In claim 17, line 6, the term “determine if the segmented” should be changed to “determine when the segmented” in order to be positively recited.
Appropriate correction is required.
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.
Claims 1-20 are rejected under 35 U.S.C. 101
Regarding Independent Claim 1 and its dependent claims 1-16
Step 1 Analysis: Claim 1 is directed to a process, which falls within one of the four statutory categories.
Step 2A Prong 1 Analysis: Claim 1 recites, in part:
“receive image data including a segmented candidate target nodule;
receive a seed point;
determine if the segmented candidate target nodule is within a threshold proximity of the seed point;
based on a determination that the segmented candidate target nodule is within the threshold proximity of the seed point, identify the segmented candidate target nodule as an identified target nodule; and
display a target nodule boundary corresponding to the identified target nodule.”
The limitations as drafted, are processes that, under broadest reasonable interpretation, covers the performance of the limitation in the mind which falls within the “Mental Processes” grouping of abstract ideas. The limitations of:
“receive image data…target nodule” is a step, under BRI, to be what a human mind can also perform through a mental process of observation and evaluation such as, the human mind can observe images of the target nodule.
“receive a seed point” is a step, under BRI, to be what a human mind can also perform through a mental process of observation and evaluation such as, the human mind can observe a seed point, and is merely data/specification of data.
“determine if…the seed point” is a step, under BRI, to be what a human mind can also perform through a mental process of observation and evaluation such as, the human mind can evaluate whether the seed point is within proximity of the target nodule.
“based on a…identified target nodule” is a step, under BRI, to be what a human mind can also perform through a mental process of observation and evaluation such as, the human mind can evaluate and identify a target nodule.
“display a target nodule...identified target nodule” is a step, under BRI, to be what a human mind can also perform through a mental process of observation and evaluation such as, the human mind can indicate, with a boundary, the identified target nodule.
Accordingly, the claim recites an abstract idea.
Step 2A Prong 2 Analysis: This judicial exception is not integrated into a practical application. particular, the claim recites the following additional element(s) –
“one or more processors; and
memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to:”
The additional elements of processors and memory - recited at a high level of generality (i.e. as a processor performing executing instructions stored, a memory storing instruction program, a computer to have computer components executing the instructions of the invention, a non-transitory computer readable medium performing storing instructions, etc.) such that they amount to no more than mere instructions to apply the exception.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim as a whole is directed to an abstract idea. Please see MPEP §2106.04.(d).III.C.
Step 2B Analysis: there are no additional elements, such as for these additional elements as indicated above, that amount to significantly more than the judicial exception. Please see MPEP §2106.05. The claim is directed to an abstract idea.
For all of the foregoing reasons, claim 1 does not comply with the requirements of 35 USC 101.
Accordingly, the dependent claims 1-16 do not provide elements that overcome the deficiencies of the independent claim 1.
Moreover, claim 2 recites, in part, “generate the segmented candidate target nodule” which merely data and further specification of data.
Claims 3-5 recite, in part, wherein clauses of merely data and further specification of data.
Claim 6 recites, in part, a wherein clause of data and further specification of data.
Claim 7, recites, in part, “provide guidance for positioning the seed point” which is an additional mental process that can be performed in the human mind, or by a human using pen and paper.
Claim 8 recites, in part, “guidance includes a graphical representation of a region” which is merely data and specification of data.
Claim 9 recites, in part, “receive user input to edit the displayed target nodule boundary… generate a revised target nodule boundary, and display the revised target nodule boundary” which is data and displaying of data which is well known in the art and does not add significantly more.
Claims 10-11 recite, in part, wherein clauses of data and displaying of data which is well known in the art and does not add significantly more.
Claim 12 recites, in part, “display a default target indicator surrounding the seed point” which is data and displaying of data which is well known in the art and does not add significantly more.
Claims 13 and 14 recite, in part, wherein clauses of data and further specification of data.
Claim 15 recites, in part, “receive a target engagement location indicator” which is an additional mental process that can be performed in the human mind and which is data/specification of data.
Claim 16 recites, in part, “plan an instrument route” which is a mental process that can be performed in the human mind, or by a human using pen and paper.
Accordingly, the dependent claims 2-16 are not patent eligible under 101.
Regarding the independent claim 17 and its dependent claims 18-20:
The independent claim 17 recites analogous limitations to the independent claim 1 hence, rejected under 101 for these analogous limitations for the reasons presented above.
Moreover, claim 17 recites further features of “A non-transitory machine-readable medium comprising a plurality of machine- readable instructions which when executed by one or more processors associated with a planning workstation are adapted to cause the one or more processors to perform a method comprising: receiving image data including a segmented candidate target nodule; receiving a seed point; determining if the segmented candidate target nodule is within a threshold proximity of the seed point; based on a determination that the segmented candidate target nodule is within the threshold proximity of the seed point, identifying the segmented candidate target nodule as an identified target nodule; and displaying a target nodule boundary corresponding to the identified target nodule” to be additional elements of generic computer/system and component components recited at high level of generality to perform generic well-known functions such as processor executing instructions stored in a memory, and these receiving, determining/identifying, and displaying steps to be merely data/specification of data and to be mental processes that can be performed in the human mind, or by a human using pen and paper.
For all of the foregoing reasons, claim 17 does not comply with the requirements of 35 USC 101.
Accordingly, the dependent claims 18-20 do not provide elements that overcome the deficiencies of the independent claim 17.
Moreover, claim 18 recites, in part, “generate the segmented candidate target nodule” which merely data and further specification of data.
Claims 19-20 recite, in part, wherein clauses of merely data and further specification of data.
Accordingly, the dependent claims 17-20 are not patent eligible under 101.
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.
Claims 1-2, 6-9, 12, 15, and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over BANERJEE et al. (US 20150097868 A1), hereinafter referenced as BANERJEE, in view of BORNEMANN et al. (US 20070217668 A1), hereinafter referenced as BORNEMANN.
Regarding claim 1, BANERJEE explicitly teaches a system comprising (Fig. 1. Paragraph [0016]-BANERJEE discloses an oncology workflow):
one or more processors (Fig. 1. Paragraph [0038]-BANERJEE discloses the illustrative workstation 30 is embodied by a computer 34 that includes an electronic data processor (not shown) and suitable user input devices such as an illustrative keyboard 36, a mouse, or so forth. Further in Paragraph [0038]-BANERJEE discloses the electronic data processor of the imaging visualization workstation may be local, e.g. a single-core or multi-core microprocessor and associated electronic components disposed inside the case of a personal computer, desktop computer, tablet computer, or the like, or may be embodied as a distributed electronic data processor, e.g. the workstation may comprise a "dumb terminal" connected via wired and/or wireless link with a network server that performs the electronic data processing.); and
memory having computer readable instructions stored thereon (Fig. 1. Paragraph [0039]-BANERJEE discloses the non-transitory storage medium storing the executable instructions may, for example, include: a hard disk drive or other magnetic storage medium; an optical disk or other optical storage medium; a flash memory, random access memory (RAM), read-only memory (ROM), or other electronic storage medium; or so forth.), the computer readable instructions, when executed by the one or more processors, cause the system to (Fig. 1. Paragraph [0039]-BANERJEE discloses as a non-transitory storage medium storing instructions executable by the illustrative computer 34 or other electronic data processing device to perform the disclosed processing and visualizations.):
display a target nodule boundary corresponding to the identified target nodule (Fig. 1. Paragraph [0043]-BANERJEE disclose when the medical image is displayed and the oncologist selects a particular lesion L (for example, by clicking on the lesion L using a mouse), the contents of the feature vectors P.sub.I(L) and P.sub.M(L) are queried and presented as a pop-up table or other suitable representation (wherein a lesion is the identified target nodule).).
BANERJEE fails to explicitly teach receive image data including a segmented candidate target nodule; receive a seed point; determine if the segmented candidate target nodule is within a threshold proximity of the seed point; based on a determination that the segmented candidate target nodule is within the threshold proximity of the seed point, identify the segmented candidate target nodule as an identified target nodule; and.
However, BORNEMANN explicitly teaches receive image data including a segmented candidate target nodule (Fig. 7. Paragraph [0278]- BORNEMANN discloses the volume of any segmented object can be determined according to the invention. Furthermore, instead of a CT data set, the object can be segmented in another data set, for example, a MR or ultrasonic image data set (wherein the segmented object is a segmented candidate target nodule.).);
receive a seed point (Paragraph [0196]-BORNEMANN discloses the seed point S can be set by a user, for example, a radiologist, or it can be set automatically, for example, in the center of the VOI.);
determine if the segmented candidate target nodule is within a threshold proximity of the seed point (Figs. 2-3. Paragraph [0200]-BORNEMANN discloses in step 101 an initial segmentation is performed using a region growing algorithm with a fixed predetermined lower threshold starting from the seed point S. Further in Paragraph [0200]-BORNEMANN discloses the result of step 101 is an initial set of voxels N.sub.0, i.e., a first set of voxels, the first estimate of the nodule region. The initial set of voxels N.sub.0 is indicated by the thick continuous line in FIG. 2b which surrounds the initial set of voxels N.sub.0.);
based on a determination that the segmented candidate target nodule is within the threshold proximity of the seed point (Figs. 2-3. Paragraph [0200]-BORNEMANN discloses in step 101 an initial segmentation is performed using a region growing algorithm with a fixed predetermined lower threshold starting from the seed point S. Further in Paragraph [0200]-BORNEMANN discloses the result of step 101 is an initial set of voxels N.sub.0, i.e., a first set of voxels, the first estimate of the nodule region. The initial set of voxels N.sub.0 is indicated by the thick continuous line in FIG. 2b which surrounds the initial set of voxels N.sub.0.), identify the segmented candidate target nodule as an identified target nodule (Figs. 2-3. Paragraph [0200]-BORNEMANN discloses the result of step 101 is an initial set of voxels N.sub.0, i.e., a first set of voxels, the first estimate of the nodule region. The initial set of voxels N.sub.0 is indicated by the thick continuous line in FIG. 2b which surrounds the initial set of voxels N.sub.0.); and
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of BORNEMANN of receive image data including a segmented candidate target nodule; receive a seed point; determine if the segmented candidate target nodule is within a threshold proximity of the seed point; based on a determination that the segmented candidate target nodule is within the threshold proximity of the seed point, identify the segmented candidate target nodule as an identified target nodule; and.
Wherein having BANERJEE’s clinical imaging system receive image data including a segmented candidate target nodule; receive a seed point; determine if the segmented candidate target nodule is within a threshold proximity of the seed point; based on a determination that the segmented candidate target nodule is within the threshold proximity of the seed point, identify the segmented candidate target nodule as an identified target nodule; and.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while BORNEMANN assesses nodule growth quickly and reliably. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and BORNEMANN et al. (US 20070217668 A1), Paragraph [0006].
Regarding claim 2, BANERJEE in view of BORNEMANN explicitly teach the system of claim 1, BANERJEE further explicitly teaches wherein the computer readable instructions, when executed by the one or more processors (Fig. 1. Paragraph [0039]-BANERJEE discloses as a non-transitory storage medium storing instructions executable by the illustrative computer 34 or other electronic data processing device to perform the disclosed processing and visualizations.),
BANERJEE fails to explicitly teach further cause the system to segment the image data to generate the segmented candidate target nodule.
However, BORNEMANN explicitly teaches further cause the system to segment the image data to generate the segmented candidate target nodule (Figs. 2-3. Paragraph [0200]-BORNEMANN discloses in step 101 an initial segmentation is performed using a region growing algorithm with a fixed predetermined lower threshold starting from the seed point S. Further in Paragraph [0200]-BORNEMANN discloses the result of step 101 is an initial set of voxels N.sub.0, i.e., a first set of voxels, the first estimate of the nodule region. The initial set of voxels N.sub.0 is indicated by the thick continuous line in FIG. 2b which surrounds the initial set of voxels N.sub.0.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of BORNEMANN of further cause the system to segment the image data to generate the segmented candidate target nodule.
Wherein having BANERJEE’s clinical imaging system further cause the system to segment the image data to generate the segmented candidate target nodule.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while BORNEMANN assesses nodule growth quickly and reliably. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and BORNEMANN et al. (US 20070217668 A1), Paragraph [0006].
Regarding claim 6, BANERJEE in view of BORNEMANN explicitly teach the system of claim 1, BANERJEE fails to explicitly teach wherein receiving the seed point includes receiving three-dimensional coordinates corresponding to the seed point.
However, BORNEMANN explicitly teaches wherein receiving the seed point includes receiving three-dimensional coordinates corresponding to the seed point (Paragraph [0217]-BORNEMANN discloses in step 107 the position of the seed point S within the [volume of interest] VOI is optimized (wherein a point in a VOI is a three-dimensional coordinate).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of BORNEMANN of wherein receiving the seed point includes receiving three-dimensional coordinates corresponding to the seed point.
Wherein having BANERJEE’s clinical imaging system wherein receiving the seed point includes receiving three-dimensional coordinates corresponding to the seed point.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while BORNEMANN assesses nodule growth quickly and reliably. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and BORNEMANN et al. (US 20070217668 A1), Paragraph [0006].
Regarding claim 7, BANERJEE in view of BORNEMANN explicitly teach the system of claim 1, BANERJEE further explicitly teaches wherein the computer readable instructions, when executed by the one or more processors (Fig. 1. Paragraph [0039]-BANERJEE discloses as a non-transitory storage medium storing instructions executable by the illustrative computer 34 or other electronic data processing device to perform the disclosed processing and visualizations.).
BANERJEE fails to explicitly teach further cause the system to provide guidance for positioning the seed point.
However, BORNEMANN explicitly teaches further cause the system to provide guidance for positioning the seed point (Fig. 2. Paragraph [0197]-BORNEMAN discloses the seed correction mechanism searches for the voxel, which is from a group of voxels fulfilling a threshold criterion the closest one with respect to the initial seed point. The threshold criterion can comprise upper and lower thresholds, wherein it is known, that voxel values of the object are located within the range defined by these lower and upper thresholds. Furthermore, a range with a predetermined width centered around the value of the center voxel of the VOI can be defined, wherein the seed correction mechanism searches for a voxel, which is from the voxels, whose voxel values are located within this range, the closest one with respect to the initial seed point.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of BORNEMANN of further cause the system to provide guidance for positioning the seed point.
Wherein having BANERJEE’s clinical imaging system further cause the system to provide guidance for positioning the seed point.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while BORNEMANN assesses nodule growth quickly and reliably. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and BORNEMANN et al. (US 20070217668 A1), Paragraph [0006].
Regarding claim 8, BANERJEE in view of BORNEMANN explicitly teach the system of claim 7, BANERJEE fails to explicitly teach wherein the guidance includes a graphical representation of a region that includes the segmented candidate target nodule.
However, BORNEMANN explicitly teaches wherein the guidance includes a graphical representation of a region that includes the segmented candidate target nodule (Fig. 2, illustrates steps of segmenting nodule. Paragraph [0197]-BORNEMAN discloses the seed correction mechanism searches for the voxel, which is from a group of voxels fulfilling a threshold criterion the closest one with respect to the initial seed point. The threshold criterion can comprise upper and lower thresholds, wherein it is known, that voxel values of the object are located within the range defined by these lower and upper thresholds. Furthermore, a range with a predetermined width centered around the value of the center voxel of the VOI can be defined, wherein the seed correction mechanism searches for a voxel, which is from the voxels, whose voxel values are located within this range, the closest one with respect to the initial seed point.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of BORNEMANN of wherein the guidance includes a graphical representation of a region that includes the segmented candidate target nodule.
Wherein having BANERJEE’s clinical imaging system wherein the guidance includes a graphical representation of a region that includes the segmented candidate target nodule.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while BORNEMANN assesses nodule growth quickly and reliably. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and BORNEMANN et al. (US 20070217668 A1), Paragraph [0006].
Regarding claim 9, BANERJEE in view of BORNEMANN explicitly teach the system of claim 1, BANERJEE further explicitly teaches and display the revised target nodule boundary (Fig. 1. Paragraph [0043]-BANERJEE disclose when the medical image is displayed and the oncologist selects a particular lesion L (for example, by clicking on the lesion L using a mouse), the contents of the feature vectors P.sub.I(L) and P.sub.M(L) are queried and presented as a pop-up table or other suitable representation (wherein a lesion is the target nodule).).
BANERJEE fails to explicitly teach wherein the computer readable instructions, when executed by the one or more processors, further cause the system to receive user input to edit the displayed target nodule boundary, generate a revised target nodule boundary.
However, BORNEMANN explicitly teaches wherein the computer readable instructions, when executed by the one or more processors, further cause the system to receive user input to edit the displayed target nodule boundary (Fig. 2. Paragraph [0196]-BORNEMANN discloses the seed point S can be set by a user, for example, a radiologist, or it can be set automatically, for example, in the center of the VOI. If the seed point S is not located on the object, a simple seed correction mechanism can be used to ensure that the seed point S is located on the object.), generate a revised target nodule boundary (Fig. 2. Paragraph [0197]-BORNEMANN discloses the seed correction mechanism searches for the voxel, which is from a group of voxels fulfilling a threshold criterion the closest one with respect to the initial seed point. The threshold criterion can comprise upper and lower thresholds, wherein it is known, that voxel values of the object are located within the range defined by these lower and upper thresholds. Furthermore, a range with a predetermined width centered around the value of the center voxel of the VOI can be defined, wherein the seed correction mechanism searches for a voxel, which is from the voxels, whose voxel values are located within this range, the closest one with respect to the initial seed point.),
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of BORNEMANN of wherein the computer readable instructions, when executed by the one or more processors, further cause the system to receive user input to edit the displayed target nodule boundary, generate a revised target nodule boundary.
Wherein having BANERJEE’s clinical imaging system wherein the computer readable instructions, when executed by the one or more processors, further cause the system to receive user input to edit the displayed target nodule boundary, generate a revised target nodule boundary.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while BORNEMANN assesses nodule growth quickly and reliably. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and BORNEMANN et al. (US 20070217668 A1), Paragraph [0006].
Regarding claim 12, BANERJEE in view of BORNEMANN explicitly teach the system of claim 1, BANERJEE fails to explicitly teach wherein the computer readable instructions, when executed by the one or more processors, further cause the system to display a default target indicator surrounding the seed point, wherein the displaying is based on a determination that the segmented candidate target nodule is not within the threshold proximity of the seed point.
However, BORNEMANN explicitly teaches wherein the computer readable instructions, when executed by the one or more processors, further cause the system to display a default target indicator surrounding the seed point (Fig 7, illustrates an indicator of the nodule core on which the seed point is located. Paragraph [0281]-BORNEMANN discloses the nodule core NC, a parenchyma area PC and a partial volume region PV are automatically identified by their distance from the boundaries of the final segmentation result N.sub.*. The three different areas NC, PC and PV are depicted in FIG. 7. The area NC is located within the nodule, the area PC surrounds the boundary of the segmented object, and the area PV is located between the areas PC and NC.),
wherein the displaying is based on a determination that the segmented candidate target nodule is not within the threshold proximity of the seed point (Figs. 2 and 7. Paragraph [0272]-BORNEMANN discloses to define an outer set PC of voxels comprising voxels arranged outside the segmented object and having a distance from the boundary of the segmented object which is larger than the predetermined minimum distance).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of BORNEMANN of wherein the computer readable instructions, when executed by the one or more processors, further cause the system to display a default target indicator surrounding the seed point, wherein the displaying is based on a determination that the segmented candidate target nodule is not within the threshold proximity of the seed point.
Wherein having BANERJEE’s clinical imaging system wherein the computer readable instructions, when executed by the one or more processors, further cause the system to display a default target indicator surrounding the seed point, wherein the displaying is based on a determination that the segmented candidate target nodule is not within the threshold proximity of the seed point.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while BORNEMANN assesses nodule growth quickly and reliably. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and BORNEMANN et al. (US 20070217668 A1), Paragraph [0006].
Regarding claim 15, BANERJEE in view of BORNEMANN explicitly teach the system of claim 1, BANERJEE further explicitly teaches wherein the computer readable instructions, when executed by the one or more processors (Fig. 1. Paragraph [0039]-BANERJEE discloses as a non-transitory storage medium storing instructions executable by the illustrative computer 34 or other electronic data processing device to perform the disclosed processing and visualizations.),
BANERJEE fails to explicitly teach further cause the system to receive a target engagement location indicator for the identified target nodule.
However, BORNEMANN explicitly teaches further cause the system to receive a target engagement location indicator for the identified target nodule (Fig. 2h. Paragraph [0255]-BORNEMANN discloses in FIG. 2h the final segmentation result N.sub.* is indicated by a thick continuous line surrounding the final segmentation result (wherein the final segmentation result is the target engagement location indicator)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of BORNEMANN of further cause the system to receive a target engagement location indicator for the identified target nodule.
Wherein having BANERJEE’s clinical imaging system further cause the system to receive a target engagement location indicator for the identified target nodule.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while BORNEMANN assesses nodule growth quickly and reliably. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and BORNEMANN et al. (US 20070217668 A1), Paragraph [0006].
Regarding claim 17, BANERJEE explicitly teaches a non-transitory machine-readable medium (Fig. 1. Paragraph [0039]-BANERJEE discloses as a non-transitory storage medium storing instructions executable by the illustrative computer 34 or other electronic data processing device to perform the disclosed processing and visualizations.) comprising a plurality of machine- readable instructions which when executed by one or more processors associated with a planning workstation are adapted to cause the one or more processors to perform a method comprising (Fig. 1. Paragraph [0038]-BANERJEE discloses the illustrative workstation 30 is embodied by a computer 34 that includes an electronic data processor (not shown) and suitable user input devices such as an illustrative keyboard 36, a mouse, or so forth. Further in Paragraph [0038]-BANERJEE discloses the electronic data processor of the imaging visualization workstation may be local, e.g. a single-core or multi-core microprocessor and associated electronic components disposed inside the case of a personal computer, desktop computer, tablet computer, or the like, or may be embodied as a distributed electronic data processor, e.g. the workstation may comprise a "dumb terminal" connected via wired and/or wireless link with a network server that performs the electronic data processing.):
displaying a target nodule boundary corresponding to the identified target nodule (Fig. 1. Paragraph [0043]-BANERJEE disclose when the medical image is displayed and the oncologist selects a particular lesion L (for example, by clicking on the lesion L using a mouse), the contents of the feature vectors P.sub.I(L) and P.sub.M(L) are queried and presented as a pop-up table or other suitable representation (wherein a lesion is the identified target nodule).).
BANERJEE fails to explicitly teach receiving a seed point; determining if the segmented candidate target nodule is within a threshold proximity of the seed point; based on a determination that the segmented candidate target nodule is within the threshold proximity of the seed point, identifying the segmented candidate target nodule as an identified target nodule; and.
However, BORNEMANN explicitly teaches receiving image data including a segmented candidate target nodule (Fig. 7. Paragraph [0278]- BORNEMANN discloses the volume of any segmented object can be determined according to the invention. Furthermore, instead of a CT data set, the object can be segmented in another data set, for example, a MR or ultrasonic image data set (wherein the segmented object is a segmented candidate target nodule.).);
receiving a seed point (Paragraph [0196]-BORNEMANN discloses the seed point S can be set by a user, for example, a radiologist, or it can be set automatically, for example, in the center of the VOI.);
determining if the segmented candidate target nodule is within a threshold proximity of the seed point (Figs. 2-3. Paragraph [0200]-BORNEMANN discloses in step 101 an initial segmentation is performed using a region growing algorithm with a fixed predetermined lower threshold starting from the seed point S. Further in Paragraph [0200]-BORNEMANN discloses the result of step 101 is an initial set of voxels N.sub.0, i.e., a first set of voxels, the first estimate of the nodule region. The initial set of voxels N.sub.0 is indicated by the thick continuous line in FIG. 2b which surrounds the initial set of voxels N.sub.0.);
based on a determination that the segmented candidate target nodule is within the threshold proximity of the seed point (Figs. 2-3. Paragraph [0200]-BORNEMANN discloses in step 101 an initial segmentation is performed using a region growing algorithm with a fixed predetermined lower threshold starting from the seed point S. Further in Paragraph [0200]-BORNEMANN discloses the result of step 101 is an initial set of voxels N.sub.0, i.e., a first set of voxels, the first estimate of the nodule region. The initial set of voxels N.sub.0 is indicated by the thick continuous line in FIG. 2b which surrounds the initial set of voxels N.sub.0.), identifying the segmented candidate target nodule as an identified target nodule (Figs. 2-3. Paragraph [0200]-BORNEMANN discloses the result of step 101 is an initial set of voxels N.sub.0, i.e., a first set of voxels, the first estimate of the nodule region. The initial set of voxels N.sub.0 is indicated by the thick continuous line in FIG. 2b which surrounds the initial set of voxels N.sub.0.); and
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE of a non-transitory machine-readable medium comprising a plurality of machine- readable instructions which when executed by one or more processors associated with a planning workstation are adapted to cause the one or more processors to perform a method comprising: displaying a target nodule boundary corresponding to the identified target nodule, with the teachings of BORNEMANN of receiving a seed point; determining if the segmented candidate target nodule is within a threshold proximity of the seed point; based on a determination that the segmented candidate target nodule is within the threshold proximity of the seed point, identifying the segmented candidate target nodule as an identified target nodule; and.
Wherein having BANERJEE’s clinical imaging system receiving a seed point; determining if the segmented candidate target nodule is within a threshold proximity of the seed point; based on a determination that the segmented candidate target nodule is within the threshold proximity of the seed point, identifying the segmented candidate target nodule as an identified target nodule; and.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while BORNEMANN assesses nodule growth quickly and reliably. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and BORNEMANN et al. (US 20070217668 A1), Paragraph [0006].
Regarding claim 18, BANERJEE in view of BORNEMANN explicitly teach the non-transitory machine-readable medium of claim 17, BANERJEE fails to explicitly teach wherein the method further comprises segmenting the image data to generate the segmented candidate target nodule.
However, BORNEMANN explicitly teaches wherein the method further comprises segmenting the image data to generate the segmented candidate target nodule (Figs. 2-3. Paragraph [0200]-BORNEMANN discloses in step 101 an initial segmentation is performed using a region growing algorithm with a fixed predetermined lower threshold starting from the seed point S. Further in Paragraph [0200]-BORNEMANN discloses the result of step 101 is an initial set of voxels N.sub.0, i.e., a first set of voxels, the first estimate of the nodule region. The initial set of voxels N.sub.0 is indicated by the thick continuous line in FIG. 2b which surrounds the initial set of voxels N.sub.0.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE of a non-transitory machine-readable medium comprising a plurality of machine- readable instructions which when executed by one or more processors associated with a planning workstation are adapted to cause the one or more processors to perform a method comprising: displaying a target nodule boundary corresponding to the identified target nodule, with the teachings of BORNEMANN of wherein the method further comprises segmenting the image data to generate the segmented candidate target nodule.
Wherein having BANERJEE’s clinical imaging system wherein the method further comprises segmenting the image data to generate the segmented candidate target nodule.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while BORNEMANN assesses nodule growth quickly and reliably. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and BORNEMANN et al. (US 20070217668 A1), Paragraph [0006].
Claims 3-5, 16, 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over BANERJEE et al. (US 20150097868 A1), hereinafter referenced as BANERJEE, in view of BORNEMANN et al. (US 20070217668 A1), hereinafter referenced as BORNEMANN, and further in view WIEMKER et al. (US 20140344742 A1), hereinafter referenced as WIEMKER.
Regarding claim 3, BANERJEE in view of BORNEMANN explicitly teach the system of claim 1, BANERJEE in view of BORNEMANN fail to explicitly teach wherein the image data includes pre-operative image data.
However, WIEMKER explicitly teaches wherein the image data includes pre-operative image data (Fig. 1. Paragraph [0034]-WIEMKER discloses the images may include preoperative images, real-time camera images and/or real-time intra-operative images.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE in view of BORNEMANN of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of WIEMKER of wherein the image data includes pre-operative image data
Wherein having BANERJEE’s clinical imaging system wherein the image data includes pre-operative image data.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while WIEMKER fully automated path planning between a target and a trachea is desirable. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and WIEMKER et al. (US 20140344742 A1), Paragraph [0005].
Regarding claim 4, BANERJEE in view of BORNEMANN explicitly teach the system of claim 1, BANERJEE in view of BORNEMANN fail to explicitly teach wherein the image data includes intra-operative image data
However, WIEMKER explicitly teaches wherein the image data includes intra-operative image data (Fig. 1. Paragraph [0034]-WIEMKER discloses the images may include preoperative images, real-time camera images and/or real-time intra-operative images.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE in view of BORNEMANN of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of WIEMKER of wherein the image data includes intra-operative image data.
Wherein having BANERJEE’s clinical imaging system wherein the image data includes intra-operative image data.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while WIEMKER fully automated path planning between a target and a trachea is desirable. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and WIEMKER et al. (US 20140344742 A1), Paragraph [0005].
Regarding claim 5, BANERJEE in view of BORNEMANN explicitly teach the system of claim 1, BANERJEE in view of BORNEMANN fail to explicitly teach wherein the image data includes pre-operative and intra-operative image data.
However, WIEMKER explicitly teaches wherein the image data includes pre-operative and intra-operative image data (Fig. 1. Paragraph [0034]-WIEMKER discloses the images may include preoperative images, real-time camera images and/or real-time intra-operative images.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE in view of BORNEMANN of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of WIEMKER of wherein the image data includes pre-operative and intra-operative image data.
Wherein having BANERJEE’s clinical imaging system wherein the image data includes pre-operative and intra-operative image data.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while WIEMKER fully automated path planning between a target and a trachea is desirable. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and WIEMKER et al. (US 20140344742 A1), Paragraph [0005].
Regarding claim 16, BANERJEE in view of BORNEMANN explicitly teach the system of claim 15, BANERJEE further explicitly teaches wherein the computer readable instructions, when executed by the one or more processors (Fig. 1. Paragraph [0039]-BANERJEE discloses as a non-transitory storage medium storing instructions executable by the illustrative computer 34 or other electronic data processing device to perform the disclosed processing and visualizations.),
BANERJEE fails to explicitly teach further cause the system to plan an instrument route to the target engagement location indicator.
However, WIEMKER explicitly teaches further cause the system to plan an instrument route to the target engagement location indicator (Fig 4A-4B. Paragraph [0024]-WIEMKER discloses the viewports offer oblique reformats to show, for each point in the Endoluminal-View, which tissue would be traversed if a virtual needle would be advanced through a pathway wall point being displayed in the image pane. This serves to find an appropriate biopsy path leading to a target (e.g., a targeted tumor or lymph node) while avoiding critical tissues and vessels.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE in view of BORNEMANN of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of WIEMKER of further cause the system to plan an instrument route to the target engagement location indicator.
Wherein having BANERJEE’s clinical imaging system further cause the system to plan an instrument route to the target engagement location indicator.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while WIEMKER fully automated path planning between a target and a trachea is desirable. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and WIEMKER et al. (US 20140344742 A1), Paragraph [0005].
Regarding claim 19, BANERJEE in view of BORNEMANN explicitly teach the non-transitory machine-readable medium of claim 17, BANERJEE in view of BORNEMANN fail to explicitly teach wherein the image data includes pre-operative image data.
However, WIEMKER explicitly teaches wherein the image data includes pre-operative image data (Fig. 1. Paragraph [0034]-WIEMKER discloses the images may include preoperative images, real-time camera images and/or real-time intra-operative images.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE in view of BORNEMANN of a non-transitory machine-readable medium comprising a plurality of machine- readable instructions which when executed by one or more processors associated with a planning workstation are adapted to cause the one or more processors to perform a method comprising: displaying a target nodule boundary corresponding to the identified target nodule, with the teachings of WIEMKER of wherein the image data includes pre-operative image data.
Wherein having BANERJEE’s clinical imaging system wherein the image data includes pre-operative image data.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while WIEMKER fully automated path planning between a target and a trachea is desirable. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and WIEMKER et al. (US 20140344742 A1), Paragraph [0005].
Regarding claim 20, BANERJEE in view of BORNEMANN explicitly teach the non-transitory machine-readable medium of claim 17, BANERJEE in view of BORNEMANN fail to explicitly teach wherein the image data includes intra-operative image data.
However, WIEMKER explicitly teaches wherein the image data includes intra-operative image data (Fig. 1. Paragraph [0034]-WIEMKER discloses the images may include preoperative images, real-time camera images and/or real-time intra-operative images.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE in view of BORNEMANN of a non-transitory machine-readable medium comprising a plurality of machine- readable instructions which when executed by one or more processors associated with a planning workstation are adapted to cause the one or more processors to perform a method comprising: displaying a target nodule boundary corresponding to the identified target nodule, with the teachings of WIEMKER of wherein the image data includes intra-operative image data.
Wherein having BANERJEE’s clinical imaging system wherein the image data includes intra-operative image data.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while WIEMKER fully automated path planning between a target and a trachea is desirable. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and WIEMKER et al. (US 20140344742 A1), Paragraph [0005].
Claims 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over BANERJEE et al. (US 20150097868 A1), hereinafter referenced as BANERJEE, in view of BORNEMANN et al. (US 20070217668 A1), hereinafter referenced as BORNEMANN, and further in view of MAO et al. (US 20030152262 A1), hereinafter referenced as MAO.
Regarding claim 10, BANERJEE in view of BORNEMANN explicitly teach the system of claim 9, BANERJEE in view of BORNEMANN fail to explicitly teach wherein editing the displayed target nodule boundary includes extending a boundary wall if a cursor is inside the target nodule boundary.
However, MAO explicitly teaches wherein editing the displayed target nodule boundary includes extending a boundary wall if a cursor is inside the target nodule boundary (Fig. 1. Paragraph [0054]-MAO discloses the user physically retracts the mouse, causing a decrease in the iteration variable and a corresponding retraction in the region. By physically moving the mouse, the user may adjust the iteration variable, thereby extending or retracting the region, until an optimal region is reached. The optimal region selects as much of the feature of interest as is possible without selecting a significant number of points corresponding to unwanted artifacts.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE in view of BORNEMANN of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of MAO of wherein editing the displayed target nodule boundary includes extending a boundary wall if a cursor is inside the target nodule boundary.
Wherein having BANERJEE’s clinical imaging system wherein editing the displayed target nodule boundary includes extending a boundary wall if a cursor is inside the target nodule boundary.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while MAO there remains a need for a system and method of quickly and easily analyzing and manipulating computer-generated images in order to filter out as much irrelevant information as possible from the images and display only the region of interest. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and MAO et al. (US 20030152262 A1), Paragraph [0005].
Regarding claim 11, BANERJEE in view of BORNEMANN explicitly teach the system of claim 9. BANERJEE in view of BORNEMANN fail to explicitly teach wherein editing the displayed target nodule boundary includes retracting a boundary wall if a cursor is outside the target nodule boundary.
However, MAO explicitly teaches wherein editing the displayed target nodule boundary includes retracting a boundary wall if a cursor is outside the target nodule boundary (Fig. 1. Paragraph [0054]-MAO discloses the user physically retracts the mouse, causing a decrease in the iteration variable and a corresponding retraction in the region. By physically moving the mouse, the user may adjust the iteration variable, thereby extending or retracting the region, until an optimal region is reached. The optimal region selects as much of the feature of interest as is possible without selecting a significant number of points corresponding to unwanted artifacts.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE in view of BORNEMANN of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of MAO of wherein editing the displayed target nodule boundary includes extending a boundary wall if a cursor is inside the target nodule boundary.
Wherein having BANERJEE’s clinical imaging system wherein editing the displayed target nodule boundary includes extending a boundary wall if a cursor is inside the target nodule boundary.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and BORNEMANN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while MAO there remains a need for a system and method of quickly and easily analyzing and manipulating computer-generated images in order to filter out as much irrelevant information as possible from the images and display only the region of interest. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and MAO et al. (US 20030152262 A1), Paragraph [0005].
Claims 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over BANERJEE et al. (US 20150097868 A1), hereinafter referenced as BANERJEE, in view of BORNEMANN et al. (US 20070217668 A1), hereinafter referenced as BORNEMANN, and further in view of VISWANATHAN et al. (US 20060041180 A1), hereinafter referenced as VISWANATHAN.
Regarding claim 13, BANERJEE in view of BORNEMANN explicitly teach the system of claim 12, BANERJEE in view of BORNEMANN fail to explicitly teach wherein the default target indicator has a three- dimensional ellipsoid shape.
However, VISWANATHAN explicitly teaches wherein the default target indicator has a three- dimensional ellipsoid shape (Fig. 33 Paragraph [0199]-VISWANATHAN discloses the object navigation pane 836 has a representation 940 of a three-dimensional object. This three dimensional object is preferably a sphere, but it could be some other shape such as an ellipse or a cube. There are preferably indicators on the surface of the three dimensional object to indicate the corresponding directions in the operating region in the subject).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE in view of BORNEMANN of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of VISWANATHAN of wherein the default target indicator has a three- dimensional ellipsoid shape.
Wherein having BANERJEE’s clinical imaging system wherein the default target indicator has a three- dimensional ellipsoid shape.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and VISWANATHAN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while VISWANATHAN provides an easy way for a physician to visualize the procedure site. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and VISWANATHAN et al. (US 20060041180 A1), Paragraph [0003].
Regarding claim 14, BANERJEE in view of BORNEMANN and further in view of VISWANATHAN explicitly teach the system of claim 13, BANERJEE in view of BORNEMANN fail to explicitly teach wherein the three-dimensional ellipsoid shape is adjustable.
However, VISWANATHAN explicitly teaches wherein the three-dimensional ellipsoid shape is adjustable (Fig. 33 Paragraph [0199]-VISWANATHAN discloses the object navigation pane 836 has a representation 940 of a three-dimensional object. This three dimensional object is preferably a sphere, but it could be some other shape such as an ellipse or a cube. There are preferably indicators on the surface of the three dimensional object to indicate the corresponding directions in the operating region in the subject Further in paragraph [0202]-VISWANATHAN discloses the rotation button 948 toggles between a rotation mode in which the cursor can be manipulated by a control device such as mouse, joystick, or keyboard to grab and rotate the representation 940 of the object, and a selection mode in which the cursor can be manipulated by a control device such as a mouse, joystick, or keyboard, to select a point of the surface of the representation 940 of the object. ).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BANERJEE in view of BORNEMANN of a system comprising: one or more processors; and memory having computer readable instructions stored thereon, the computer readable instructions, when executed by the one or more processors, cause the system to: display a target nodule boundary corresponding to the identified target nodule with the teachings of VISWANATHAN of wherein the default target indicator has a three- dimensional ellipsoid shape.
Wherein having BANERJEE’s clinical imaging system wherein the default target indicator has a three- dimensional ellipsoid shape.
The motivation behind the modification would have been to obtain a clinical imaging system with nodule identification that enhances the accuracy of identifying nodules. Since both BANERJEE and VISWANATHAN relate to medical imaging workflows and systems, wherein BANERJEE provides spatial mapping of biopsy information based on imaging data, while VISWANATHAN provides an easy way for a physician to visualize the procedure site. Please see BANERJEE et al. (US 20150097868 A1), Paragraph [0013], and VISWANATHAN et al. (US 20060041180 A1), Paragraph [0003].
Conclusion
Listed below are the prior arts made of record and not relied upon but are considered
pertinent to applicant’s disclosure.
Wei et al (US 8837789 B2) - A procedure for image segmentation of a lung in tomosynthesis images includes determining a focal plane image of a lung from among a plurality of tomosynthesis images, determining boundaries of the lung in the focal plane image based on a sequence of best-path algorithms cascaded together, assembling the tomosynthesis images to obtain a 3D image of the lung, determining a boundary of a rib in the 3D image of the lung, and segmenting the lung based on the boundaries of the lung and the boundary of the rib. A procedure for detecting nodules in tomosynthesis images includes generating a blurred nodule template, generating a blurred vessel template and a blurred rib template, determining, based on the blurred nodule template, a nodule candidate in 3D image of a lung, and determining, based on the blurred vessel template and a blurred rib template, that the nodule candidate is a nodule.
DOUGHERTY et al. (US 20190318483 A1) - A local extension method for segmentation of anatomical treelike structures includes receiving an initial segmentation of 3D image data including an initial treelike structure. A target point in the 3D image data is defined, and a region of interest based on the target point is extracted to create a sub-image. Highly tubular voxels are detected in the sub-image, and a spillage-constrained region growing is performed using the highly tubular voxels as seed points. Connected components are extracted from the results of the region growing. The extracted components are pruned to discard components not likely to be connected to the initial treelike structure, keeping only candidate components likely to be a valid sub-tree of the initial treelike structure. The candidate components are connected to the initial treelike structure, thereby extending the initial segmentation in the region of interest.
TSUNOMORI et al. (US 20170116731 A1) - A medical image system, including: a target region extraction section which extracts a target region from a medical image obtained by X-ray imaging of a target site; a first extraction section which extracts an initial region from the target region, the initial region having a brightness value which is equal to or larger than a first reference value; a second extraction section which extracts a region having a brightness value that is equal to or smaller than a second reference value from a region including the initial region in the target region; an acquisition section which calculates areas of the target region, the region including the initial region and the region extracted by the second extraction section, and acquires an index regarding a lesion based on the calculated areas; and a display section which displays the acquired index regarding the lesion.
Kubota (US 20090092302 A1) - A method for differentiating pulmonary nodules in digitized medical images includes identifying an object of interest from a digital image of the lungs, computing a first distance map of each point of the object of interest, determining a seed point from the first distance map, starting from the seed point, growing a first region by adding successive adjacent layers of points until a background point is reached, and partitioning the first region into a nodule region and a non-nodule region.
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/ETHAN N WOLFSON/Examiner, Art Unit 2673
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673