DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
2. The information disclosure statement (IDS) submitted on September 5, 2024 is considered by the examiner.
Claim Objections
3. Claim 1 is objected to because of the following informalities: Line 1, a colon should be placed after the word “comprising” to separate the preamble from the body of the claim.
3. Claim 6 is objected to because of the following informalities: Line 4, "and/or" should be just one "and" or "or". The claim will be interpreted as an “or”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
4. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
5. Claims 9 and 16 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
6. Regarding claim 9, the Examiner is unclear as to when claim 9 is executed in respect to claim 1. Claim 9 asserts the second sample is adjusted based on a previous voxel value of the second sample. However, claim 9 is dependent on claim 1 which asserts that the second sample is adjusted based on a weighted sum of the plurality of differences wherein the plurality of differences are differences between a plurality of first opacity values in a first region of the first volume data and a plurality of corresponding second opacity values in the second region.
Does the Applicant intend for the previous voxel value to be part of the weighted sum of the plurality of differences? Or does the Applicant intend for the adjustment based on the previous voxel value to be a separate step executed after the voxel value of the second sample has been adjusted based on the weighted sum of the plurality of differences? Thus, claim 9 is unclear and will be examined as best understood.
7. Regarding claim 16, the Examiner is unclear as to when the steps of claim 16 is executed in respect to claim 1. Claim 16 discloses determining whether the plurality of first opacity values in the first region are the same and maintain the voxel value of the second sample in the second region in response to the determination. Claim 1 discloses that the second sample is adjusted based on a weighted sum of the plurality of differences wherein the plurality of differences are differences between a plurality of first opacity values in a first region of the first volume data and a plurality of corresponding second opacity values in the second region.
It is unclear if claim 16 happens before, after, or during claim 1’s iterations of determining a plurality of differences between the first opacity values and second opacity values. Does the Applicant mean that the plurality of first opacity are first checked to see if they are the same and if so, will choose to maintain the voxel value of the second sample and not determine a plurality of differences and adjust the voxel value of the second sample? Or does the Applicant mean to adjust the voxel value of the second sample based on a weighted sum of the plurality of differences and then decide to maintain the adjusted the voxel value of the second sample by ending the iterations there? Thus, claim 16 is unclear and will be examined as best understood.
Claims 9 and 16 will be examined as best understood.
Claim Rejections - 35 USC § 102
8. 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.
9. 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
10. Claim(s) 1, 6-12, 17-18, and 20 is/are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being anticipated by Noo et al. (U.S. Patent Application Publication No. 2014/0221124 A1), hereinafter referred to as Noo.
11. Regarding claim 1, Noo teaches a volumetric imaging data processing apparatus comprising processing circuitry configured to (Paragraph 33 and 41 teach a processor performs the tasks disclosed): receive first volume data comprising a plurality of first samples (Paragraph 83 and Fig. 3 step p teaches “the input data is projection data p, which may be acquired by one of the CT systems”. This discloses receiving a first volume data with a plurality of first samples);
generate second volume data based on the first volume data, the second volume data comprising a plurality of second samples, a number of the plurality of second samples being less than a number of the plurality of first samples and each of the plurality of second samples of the second volume data having a corresponding first sample of the first volume data (Paragraphs 87-88 and Fig. 3 step S10 teach “the initial image dataset is divided into blocks of mxn, or alternatively mxm voxels” and an example of “the schematic dataset having 12x12 pixels 4 is divided into nine groups 2 having 4x4 pixels each.” Paragraph 88 also teaches “the shaded pixels 6 in Fig. 5 …. define one subspace”. This discloses generating a second volume data that groups the first volume data into mn groups with each group represented by a specific voxel. Each group is a sample in the second volume dataset and each voxel in the initial 12x12 dataset can be considered a group and sample in the first volume dataset. Here, the first volume data then has 12x12 groups (samples) while the second volume data only has 9 groups (samples). Thus, the second volume data set has less samples than the first one and has a corresponding sample to the first volume data);
generate adjusted second volume data comprising a plurality of adjusted second regions, each adjusted second region being generated by performing a number of iterations of adjusting a voxel value of a second sample in a second region of the second volume data (Paragraph 89-90 teaches “the voxel values are then updated group by group”. This teaches iteratively updating the voxel values in the second volume data set. Updated voxel values teach generating adjusted second regions),
wherein in each of the number of iterations, the processing circuitry is configured to: determine a plurality of differences between a plurality of first opacity values in a first region of the first volume data and a plurality of corresponding second opacity values in the second region (Paragraph 65 teaches the voxel value are grey scale values. Paragraph 73 teaches taking the difference between the voxel values in the calculated projection dataset and projection data. The calculated projection dataset is the second volume data with second regions. The projection data is the first volume data with first regions that correspond to regions in the calculated projection data set or second regions; Paragraph 26 teaches the grayscale values are in HU which the Applicant admits teaches opacity in the Applicant’s Specification. The Applicant’s specification teaches that opacity can be the X-ray stopping power and that “X-ray stopping power is measured in Hounsfield Units (HUs)”. Thus, the grey scale voxel values teach opacity values);
and adjust the voxel value of the second sample in the second region based on a weighted sum of the plurality of differences (Abstract teaches updating voxels values for voxels in a sample in the second region based on minimizing a function consisting of a weighted sum; Paragraph 73 teaches “the difference between the calculated projection dataset and the projection data is computed, the difference is backward projected into the image space, and the backward projection is weighted and subtracted from or added to the image dataset or in particular the voxels to be updated.” This teaches a weighted sum of the plurality of differences by weighting the difference when backward projecting it. The calculated projection dataset is the second volume data with the second region and second sample and the projection data is the first volume data and first sample).
12. Regarding claim 6, Noo teaches the limitations of claim 1. Noo further teaches wherein a weighting of the weighted sum of differences is based on at least one of: a position in the first and second regions at which each of the plurality of differences is determined relative to the second sample; and/or a deviation between a first opacity value of the plurality of first opacity values and a corresponding second opacity value of the plurality of second opacity values (Paragraph 93 teaches a weighted least square model which takes the difference between Ax and g. A is the matrix mapping x, the second region samples, to the initially collected data g, first region samples. Weighted least square models assign weight depending on the deviation or variance between the values. Thus, this teaches the weighted sum of differences is based on the deviation between a first and second opacity value. The Applicant uses “at least one of” so only one of the limitations needs to be met).
13. Regarding claim 7, Noo teaches the limitations of claim 6. Noo further teaches wherein the processing circuitry is configured to assign a weighting of zero to at least one of the plurality of differences determined at a position adjacent to at least one other second sample in the second region (Paragraph 94 teaches the weighting factor of the weighted sum can be between 0 and 10. This is calculated for voxels within one group as taught in Paragraph 91 which can be adjacent to other groups or regions as seen in Figure 5 which shows multiple 4x4 groups, one marked by the 2 marker).
14. Regarding claim 8, Noo teaches the limitations of claim 1. Noo further teaches wherein the processing circuitry is configured to adjust the voxel value of the second sample by: increasing or decreasing the voxel value of the second sample based on a sign of the weighted sum of differences (Paragraph 65 teaches “updating means that the voxel value is replaced by another voxel value which should in most instances be closer to the true image than the initial voxel value “. This teaches that the weighted sum is for minimizing the difference between the computed voxel and true value; Paragraph 73 teaches "the difference is backward projected into the image space, and the backward projection is weighted and subtracted from or added to the image dataset or in particular the voxels to be updated". Since the weighted sum of differences (weighted backward projection) is subtracted from or added to the volume dataset, that increases or decreases the voxel value based on the sign of that weighted sum of differences).
15. Regarding claim 9, Noo teaches the limitations of claim 1. Noo further teaches wherein in each iteration, the processing circuitry is configured to adjust the voxel value of the second sample relative to a previous voxel value of the second sample (Paragraph 73 teaches “the difference between the calculated projection dataset and the projection data is computed, the difference is backward projected into the image space, and the backward projection is weighted and subtracted from or added to the image dataset or in particular the voxels to be updated.” The second sample are the voxels in the calculated projection dataset. This teaches adjusting the voxel value of the second sample relative to the previous voxel value of the second sample by applying the difference to the previous voxel value of the second sample).
167. Regarding claim 10, Noo teaches the limitations of claim 1. Noo further teaches wherein in a first iteration, the processing circuitry is configured to: adjust the voxel value of the second sample by an amount; determine whether a predetermined metric has been met; in response to a determination that the predetermined metric has been met, maintain a current voxel value of the second sample; or in response to a determination that the predetermined metric has not been met, perform a next iteration of adjusting a voxel value of the second sample (Paragraph 89-90 teaches iteratively adjusting the voxel values in the second volume data set by an amount; Paragraph 90 teaches continuing the iteration until a certain threshold is reached in the difference between the calculated and measured data or when a full iteration is performed. This teaches determining when a predetermined metric (a difference or iteration amount) is met and deciding whether to continue the iterations to perform another adjustment of the voxel value or to end the iterations which results in maintaining the current voxel value of the second sample).
17. Regarding claim 11, Noo teaches the limitations of claim 10. Noo further teaches wherein in each subsequent iteration, the processing circuitry is configured to: determine whether a sign of the weighted sum of the plurality of differences has changed; and in response to a determination that the sign of the weighted sum of the plurality of differences has changed, reduce an amount of adjustment to be applied to the voxel value of the second sample in a next iteration relative to an amount of adjustment applied to the voxel value of the second sample in a current iteration (Paragraph 65 teaches “updating means that the voxel value is replaced by another voxel value which should in most instances be closer to the true image than the initial voxel value “. This teaches that the weighted sum is for minimizing the difference between the computed voxel and true value; Paragraph 73 teaches "the difference is backward projected into the image space, and the backward projection is weighted and subtracted from or added to the image dataset or in particular the voxels to be updated". Since the weighted sum of differences (weighted backward projection) is subtracted from or added to the volume dataset, that increases or decreases the voxel value (iterating towards a true value) based on the sign of that weighted sum of differences; Paragraph 102 teaches the changes become small as they reach convergence. Thus, the amount of adjustment is reduced during the iterations).
18. Regarding claim 12, Noo teaches the limitations of claim 11. Noo further teaches wherein in each subsequent iteration, the processing circuitry is configured to: determine whether a predetermined metric has been met; in response to a determination that the predetermined metric has been met, maintain a current voxel value of the second sample; or in response to a determination that the predetermined metric has not been met, perform a next iteration of adjusting the voxel value of the second sample (Paragraph 90 teaches continuing the iteration until a certain threshold is reached in the difference between the calculated and measured data or when a full iteration is performed. This teaches determining when a predetermined metric (a difference or iteration amount) is met and deciding whether to continue the iterations to perform another adjustment of the voxel value or to end the iterations which results in maintaining the current voxel value of the second sample).
19. Regarding claim 17, Noo teaches the limitations of claim 1. Noo further teaches wherein the processing circuitry is configured to perform a rendering process on the adjusted second volume data (Paragraph 54 teaches “an image dataset interface for outputting the final image dataset, for example a screen, display or printer” which teaches running a rendering process on the adjusted second volume data for display).
20. Regarding claim 18, Noo teaches the limitations of claim 1. Noo further teaches wherein the first volume data comprises a plurality of first regions and the processing circuitry is configured to successively: receive at least one of the plurality of first regions (Paragraph 83 and Fig. 3 step p teaches “the input data is projection data p, which may be acquired by one of the CT systems”. This discloses receiving a first volume data with a plurality of first samples);
generate a second region based on the at least one of the plurality of first regions (Paragraphs 87-88 and Fig. 3 step S10 teach “the schematic dataset having 12x12 pixels 4 is divided into nine groups 2 having 4x4 pixels each”. This teaches generating a second volume data that groups the first volume data into mn groups. Each group teaches a sample in the second volume dataset. Each voxel in the initial 12x12 dataset can be considered a group and sample in the first volume dataset. Here, the initial dataset has 12x12 groups while the second dataset only has 9 groups. Thus, the second volume data set has less samples than the first one and has a corresponding sample to the first volume data);
and generate an adjusted second region by performing the number of iterations of adjusting a voxel value of a second sample in the second region (Paragraph 89-90 teaches “the voxel values are then updated group by group”. This teaches iteratively updating the voxel values in the second volume data set. Updated voxel values teach generating adjusted second regions).
21. Regarding claim 20, claim 20 is the method claim of apparatus claim 1 and is accordingly rejected using substantially similar rationale as to that which is set for with respect to claim 1.
Claim Rejections - 35 USC § 103
22. 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.
23. Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Noo et al. (U.S. Patent Application Publication No. 2014/0221124 A1), hereinafter referred to as Noo, as applied to claim 1 above, and further in view of Reynolds et al. (U.S. Patent Application Publication No. 2021/0375027 A1), hereinafter referred to as Reynolds, and Davies et al. (U.S. Patent Application Publication No. 2022/0172402 A1), hereinafter referred to as Davies.
Regarding claim 2, Noo teaches the limitations of claim 1. However, Noo is not relied upon for the below claim language: the apparatus wherein the processing circuitry is configured to: determine the plurality of first opacity values in the first region based on a first transfer function applied to the plurality of first samples and an interpolation used to generate first volumetric imaging data between the plurality of first samples; and determine the plurality of second opacity values in second region based on a second transfer function applied to the plurality of second samples and an interpolation used to generate second volumetric imaging data between the plurality of second samples.
Reynolds teaches the apparatus wherein the processing circuitry is configured to: determine the plurality of first opacity values in the first region based on a first transfer function applied to the plurality of first samples (Paragraph 43-44 teaches applying a transfer function to voxels in the received volumetric image data set to determine the opacity) and an interpolation used to generate first volumetric imaging data between the plurality of first samples (Paragraph 59 teaches “in rendering … a data value for a sample po int is obtained by interpolating data values of voxels in a neighborhood of the sample point.” This teaches using interpolation to generate first volumetric imaging data between a plurality of first samples);
Noo and Reynolds are considered analogous to the claimed invention as because both are in the same field of rendering volume data for display. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the apparatus of generating an adjusted second volume data taught by Noo with the transfer function and interpolation applied to the first samples taught by Reynolds in order to determine the visibility of voxels and render points that may not have existing voxel positions (Reynolds Abstract and Paragraph 59).
However, Noo and Reynolds are not relied upon for the below claim language: determining the plurality of second opacity values in second region based on a second transfer function applied to the plurality of second samples and an interpolation used to generate second volumetric imaging data between the plurality of second samples.
Davies teaches determining the plurality of second opacity values in second region based on a second transfer function applied to the plurality of second samples (Paragraph 92 teaches a transfer function maps the voxel values to corresponding opacity values. The transfer function is applied to the voxels in the downsized volume which is the second volume wherein the voxels in the second volume are second regions and samples) and an interpolation used to generate second volumetric imaging data between the plurality of second samples (Paragraphs 124-125 teach using interpolated data values to check visibility of the voxels in the downsized volume as part of step 44 in Figure 2 which is used to later render the second dataset in stage 46 and 47 Figure 2. Thus, interpolation is sued to generate second volumetric imaging data).
Noo, Reynolds, and Davies are considered analogous to the claimed invention as because both are in the same field of rendering volume data for display. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the apparatus of generating an adjusted second volume data taught by Noo and Reynolds with the transfer function and interpolation applied to the second samples taught by Davies in order to quickly render image data based on the opacities and gradient visibility of voxels (Davies Paragraph 1 and Paragraph 161).
24. Claim(s) 3-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Noo et al. (U.S. Patent Application Publication No. 2014/0221124 A1), hereinafter referred to as Noo, in view of Reynolds et al. (U.S. Patent Application Publication No. 2021/0375027 A1), hereinafter referred to as Reynolds, and Davies et al. (U.S. Patent Application Publication No. 2022/0172402 A1), hereinafter referred to as Davies, as applied to claim 2 above, and further in view of Shen et al. (U.S. Patent Application Publication No. 2003/0146913 A1), hereinafter referred to as Shen.
25. Regarding claim 3, Noo in view of Reynolds and Davies teaches the limitations of claim 2. However, Noo, Reynolds, and Davies are not relied upon for the below claim language: the apparatus wherein each difference of the plurality of differences comprises a subtracted difference between an average value of a group of the plurality of first opacity values and an average value of a corresponding group of the plurality of second opacity values.
Shen teaches the apparatus wherein each difference of the plurality of differences comprises a subtracted difference between an average value of a group of the plurality of first opacity values and an average value of a corresponding group of the plurality of second opacity values (Paragraphs 11-12 teach taking a difference between the group of first greyscale values and second greyscale values “where {overscore (V)}.sub.A and {overscore (V)}.sub.B are the mean of the grayscale values of all pixels in said two volumes-of-interest and the summations are over all the voxels in both said volumes-of-interest”).
Noo, Reynolds, and Davies are considered analogous to the claimed invention as because both are in the same field of rendering volume data. Shen is considered analogous to the claimed invention because both are in the same field of analyzing between volume data sets. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the apparatus of generating an adjusted second volume data taught by Noo in view of Reynolds and Davies with the difference between the averages of the first and second opacity values taught by Shen in order to roughly align the two image sets (Shen Abstract).
26. Regarding claim 4, Noo in view of Reynolds, Davies, and Shen teaches the limitations of claim 2. Noo further teaches the apparatus wherein each difference of the plurality of differences comprises a subtracted difference between at least one first opacity value of the plurality of first opacity values and at least one corresponding second opacity value of the second plurality of opacity values (Paragraph 73 teaches taking the difference between the voxel values in the calculated projection dataset and projection data. The calculated projection dataset is the second volume data with second opacity values. The projection data is the first volume data with first opacity values. Thus, this teaches taking the difference between the projection data which includes at least one opacity value in the plurality of first opacity values and the calculated projection dataset which includes at least one second opacity value in the second plurality of opacity values.).
27. Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Noo et al. (U.S. Patent Application Publication No. 2014/0221124 A1), hereinafter referred to as Noo, as applied to claim 1 above, and further in view of Choi et al. (U.S. 2013/0021341 A1), hereinafter referred to as Choi, Reynolds et al. (U.S. Patent Application Publication No. 2021/0375027 A1), hereinafter referred to as Reynolds, and Davies et al. (U.S. Patent Application Publication No. 2022/0172402 A1), hereinafter referred to as Davies.
Regarding claim 5, Noo teaches the limitations of claim 1. However, Noo is not relied upon for the below claim language: the apparatus wherein each of the plurality of differences comprises a gradient between a first opacity value of a first transfer function at a first position in the first region and a second opacity value of a second transfer function at a second position in the second region, wherein the second position in the second region corresponds to the first position in the first region.
Choi teaches the apparatus wherein each of the plurality of differences comprises a gradient between a first opacity value (Paragraph 14 teaches a “gradient between intensities of the voxels corresponding to the one of the extracted partial regions of the first volume image and the voxels corresponding to the one of the extracted partial regions of the second volume image”. The voxel intensities can be considered the opacity. The regions in the second volume image correspond to the regions in the first volume image. Thus, the voxel positions, the second and first positions, also correspond).
Noo and Choi are considered analogous to the claimed invention as because both are in the same field of rendering volume data. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the apparatus of generating adjusted second volume data taught by Noo with the gradient between a first and second region taught by Choi in order to obtain a final volume image that matches the first volume image (Choi Paragraph 123).
However, Noo and Choi are not relied upon for the below claim language: a first opacity value of a first transfer function and a second opacity value of a second transfer function.
Reynolds teaches a first opacity value of a first transfer function (Paragraph 43-44 teaches applying a transfer function to voxels in the received volumetric image data set to determine the opacity)
Noo, Choi, and Reynolds are considered analogous to the claimed invention as because both are in the same field of rendering volume data. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the apparatus of generating an adjusted second volume data taught by Noo in view of Choi with the transfer function applied to the first samples taught by Reynolds in order to determine the visibility of voxels and render points that may not have existing voxel positions (Reynolds Abstract and Paragraph 59).
However, Noo, Choi, and Reynolds are not relied upon for the below claim language: a second opacity value of a second transfer function.
Davies teaches a second opacity value of a second transfer function (Paragraph 92 teaches a transfer function maps the voxel values to corresponding opacity values. The transfer function is applied to the voxels in the downsized volume which is the second volume wherein the voxels in the second volume are second regions and samples)
Noo, Choi, Reynolds, and Davies are considered analogous to the claimed invention as because both are in the same field of rendering volume data. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the apparatus of generating an adjusted second volume data taught by Noo in view of Choi and Reynolds with the transfer function applied to the second samples taught by Davies in order to quickly render image data based on the opacities and gradient visibility of voxels (Davies Paragraph 1 and Paragraph 161).
28. Claim(s) 13-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Noo et al. (U.S. Patent Application Publication No. 2014/0221124 A1), hereinafter referred to as Noo, as applied to claim 1 above, and further in view of Shen et al. (U.S. Patent Application Publication No. 2003/0146913 A1), hereinafter referred to as Shen.
29. Regarding claim 13, Noo teaches the limitations of claim 1. Noo further teaches the apparatus wherein the processing circuitry is configured to: only adjust the voxel value of the second sample, when a combined total of the plurality of differences is above a threshold value (Paragraph 71 teaches “the step of updating the voxel values for all voxels within a sub-space includes minimizing the function until a certain threshold is reached”. Paragraph 90 teaches “depending for example on whether a certain threshold is reached in the difference between the calculated (forward-projected) projection dataset and the measured projection data, either a further full iteration is performed (step S16), or the last intermediate image dataset is made the final image dataset D18”. Thus, if the plurality of differences are not at the threshold which includes being above a threshold, then the second voxel value will be adjusted), (Paragraph 90 teaches continuing the iteration until a certain threshold is reached in the difference between the calculated and measured data. This teaches when the differences reaches a threshold, the current voxel value of the second sample is maintained by ending the updating iterations).
However, Noo is not relied upon for the below claim language: each of the plurality of differences comprising an absolute difference.
Shen teaches each of the plurality of differences comprising an absolute difference (Paragraph 13 teaches taking the absolute differences over the voxels from a first and second volume. Paragraph 7 teaches the first volume is a volume from one image set and the second volume is a corresponding region in a second image set).
Noo and Shen are considered analogous to the claimed invention as because both are in the same field of modifying voxel values in a volume image. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the apparatus of generating an adjusted second volume data taught by Noo with the absolute difference taught by Shen in order to roughly align the two image sets (Shen Abstract).
30. Regarding claim 14, Noo in view of Shen teaches the limitations of claim 13. Noo further teaches the apparatus wherein when the current voxel value of the second sample is maintained, the processing circuitry is configured to maintain one or more of the plurality of second opacity values associated with the second sample (Paragraph 90 teaches “depending for example on whether a certain threshold is reached in the difference between the calculated (forward-projected) projection dataset and the measured projection data, either a further full iteration is performed (step S16), or the last intermediate image dataset is made the final image dataset D18”. The last image set being made the final image dataset teaches one or more of the plurality of the second opacity values are maintained when the threshold is reached).
31. Regarding claim 15, Noo in view of Shen teaches the limitations of claim 13. Noo further teaches wherein when a voxel value of two or more adjacent second samples of the plurality of second samples is maintained, the processing circuitry is configured to maintain one or more of the plurality of second opacity values,
the one or more of the plurality of second opacity values being determined at one or more positions between the two or more adjacent second samples of the plurality of second samples (Paragraph 90 teaches “depending for example on whether a certain threshold is reached in the difference between the calculated (forward-projected) projection dataset and the measured projection data, either a further full iteration is performed (step S16), or the last intermediate image dataset is made the final image dataset D18”. The last image set being made the final image dataset teaches one or more of the plurality of the second opacity values are maintained when the threshold is reached. This teaches also maintaining the adjacent second samples since all the samples are maintained when the final image dataset is output).
32. Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Noo et al. (U.S. Patent Application Publication No. 2014/0221124 A1), hereinafter referred to as Noo, as applied to claim 18 above, and further in view of Bohn et al. (U.S. Patent Application Publication No. 2019/0266785 A1), hereinafter referred to as Bohn.
Regarding claim 19, Noo teaches the limitations of claim 18. However, Noo is not relied upon for the below claim language: the apparatus wherein each of the plurality of first regions is surrounded by a margin region, the margin region comprising one or more first samples from one or more neighbouring first regions of the plurality of first regions.
Bohn teaches the apparatus wherein each of the plurality of first regions is surrounded by a margin region, the margin region comprising one or more first samples from one or more neighbouring first regions of the plurality of first regions (Paragraph 54-55 and Figures 5 and 6 teach the first region 502 have a dilated boundary 600 that is used for sampling to create the downsized dataset. The dilated boundary teaches a margin region. Figure 6 teaches the dilated region 600 includes samples from neighboring first regions of the plurality of first regions).
Noo and Bohn are considered analogous to the claimed invention as because both are in the same field of rendering volume data. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the apparatus of generating an adjusted second volume data taught by Noo with the margin region taught by Bohn in order to avoid interpolation artifacts during rendering (Bohn Paragraph 54).
Allowable Subject Matter
33. Claim 16 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include 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: The combination of the prior art fails to teach the apparatus wherein the processing circuitry is configured to: detect whether the plurality of first opacity values in the first region are the same; and in response to a determination that the plurality of first opacity values in the first region are the same, maintain the voxel value of the second sample in the second region, wherein the plurality of first opacity values in the first region each comprise a fully transparent opacity value or a fully opaque opacity value.
Conclusion
34. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
- Souza et al. (U.S. Patent Application Publication No. 2009/0226067 A1) teaches adjusting a second volume data based on differences between a first and second intensity values.
- Coupe et al. (U.S. Patent Application Publication No. 2011/0044553 A1) teaches creating weighted intensity data.
- Murray et al. (U.S. Patent Application Publication NO. 2015/0022523 A1) teaches calculating opacity values for volumetric data.
35. Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTINE Y AHN whose telephone number is (571)272-0672. The examiner can normally be reached M-F 9-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alicia Harrington can be reached at (571)272-2330. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHRISTINE YERA AHN/Examiner, Art Unit 2615
/ALICIA M HARRINGTON/Supervisory Patent Examiner, Art Unit 2615