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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 02/05/2026 has been entered.
Specification
The disclosure is objected to because of the following informalities. Examiner is maintaining the objection to the title of the invention:
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
Appropriate correction is required.
Response to Amendment
Applicant’s Amendments filed on 02/05/2026 has been entered and made of record.
Currently pending Claim(s):
Independent Claim(s):
Amended Claim(s):
Cancelled Claim(s):
1–19 and 21
1 and 21
1, 11, 12 and 21
20
Response to Applicant’s Arguments
This office action is responsive to Applicant’s Arguments/Remarks Made in an Amendment received on 02/05/2026.
In view of the amendments filed on 02/05/2026 to the specification title of the invention, the specification objections still applies.
Applicant’s arguments with respect to claim(s) 1 and 21 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Examiner is removing Fischer as the primary and using Leng et al. (US 20200214619 A1) as the primary to teach acquiring a first image a plurality of second images depicting different quantified parameter information and adding Zhang et al. (US 20200303049 A1) to teach registering the first image to the second image to determine a second ROI based on the first ROI, generating a report based on second ROI of the plurality of second images and incorporating Gooding et al. (US 20140247284 A1) synchronously updating the first ROI in the second images.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claim(s) 1–4, 10–14, 18–19 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Leng et al. (US 20200214619 A1, hereafter, “Leng”) in view of Zhang et al. (US 20200303049 A1, hereafter, "Zhang”) and further in view of Gooding et al. (US 20140247284 A1, hereafter, “Gooding”).
Regarding claim 1, Leng teaches a medical image processing system, comprising a medical imaging device and a report generating device (See Leng, [Abstract], Medical imaging analysis systems are configured to perform automatic image registration algorithms that perform three-dimensional (3D), affine, and/or intensity-based co-registration of magnetic resonance imaging (MRI) data), wherein:
the medical imaging device is configured to acquire a first image and a plurality of second images of a target part (See Leng, ¶ [0027], As one example, medical imaging data 18 may represent various two-dimensional (2D) images of a prostate gland of patient 8. Each 2D image may be a different plane of the scanned tissue. That is, the medical imaging device that generates medical imaging data 18 may take multiple 2D scans, each at a different point along a third dimension. In this way, the composite of medical imaging data 18 may, in some examples, be a series of planes (e.g., “slices”) of the scanned tissue), and [transmit the first image and the plurality of second images to the report generating device]; the first image is used for depicting an anatomy structure of the target part, and each of the plurality of second images is used for depicting different quantified parameter information of the target part (See Leng, ¶ [0032], Image interpretation module 12 receives registered medical imaging data 19 and may determine one or more 2D parameter maps corresponding to the imaged tissue. A 2D parameter map may indicate the value of a parameter at each location of the scanned tissue. For instance, image interpretation module 12 may generate a parameter map for one or more of an apparent T2 (T2) parameter, an apparent diffusion coefficient (ADC) parameter, pharmacokinetic parameters K.sup.Trans, k.sub.ep, and/or an area under the gadolinium concentration time curve over 90 s (AUGC90) parameter. Note: The T2, ADC and pharmacokinetic are being interpreted as quantified parameter information);
[the report generating device is configured to identify a first region of interest (ROI) in the first image or utilize a first ROI manually circled on the first image, and configured to perform a registration for the first image and each of the plurality of second images to update the first ROI synchronously in each of the plurality of second images to obtain a second ROI in each of the plurality of second images; the second ROI in each of the plurality of second images is relevant to the first ROI in the first image;
the report generating device is further configured to generate a human readable report of the target part according to the quantified parameter information corresponding to the second ROI in each of the plurality of second images, wherein the human readable report comprises quantified parameter information of the target part in different dimensions].
However, Leng fail(s) to teach transmit the first image and the plurality of second images to the report generating device; the report generating device is configured to identify a first region of interest (ROI) in the first image or utilize a first ROI manually circled on the first image, and configured to perform a registration for the first image and each of the plurality of second images to update the first ROI synchronously in each of the plurality of second images to obtain a second ROI in each of the plurality of second images; the second ROI in each of the plurality of second images is relevant to the first ROI in the first image; the report generating device is further configured to generate a human readable report of the target part according to the quantified parameter information corresponding to the second ROI in each of the plurality of second images, wherein the human readable report comprises quantified parameter information of the target part in different dimensions.
Zhang, working in the same field of endeavor, teaches: transmit the first image and the plurality of second images to the report generating device (See Zhang, ¶ [0065], The obtaining module 410 may obtain data and/or information. In some embodiments, the obtaining module 410 may obtain imaging information from a multi-modality imaging device. The imaging information may be acquired from a scan of a subject using the multi-modality imaging device. The imaging information may include an image (e.g., a two-dimensional (2D) image, a three-dimensional (3D) image, etc.), a video (e.g., a 2D video, a 3D video, etc.), image data (e.g., image data corresponding to an image or a video), or the like. ¶ [0066], The processing module 420 may process data and/or information, and generate a diagnostic imaging report based on the processed data);
the report generating device is configured to identify a first region of interest (ROI) in the first image (See Zhang, ¶ [0073], The identification unit 520 may identify one or more ROIs with respect to the first imaging information and/or the second imaging information. In some embodiments, the identification unit 520 may identify at least one first target ROI based on the first imaging information, and determine first reporting information corresponding to the at least one first target ROI. In some embodiments, the first reporting information may include at least one of an image, text, a video, or an annotation) or utilize a first ROI manually circled on the first image (See Zhang, ¶ [0073], In some embodiments, the obtaining unit 510 may receive a region selection instruction from a user. The region selection instruction may direct the identification unit 520 to select at least one first target ROI from the at least two candidate ROIs), and configured to perform a registration for the first image and each of the plurality of second images (See Zhang, ¶ [0075], The identification unit 520 may perform the image fusion or image registration between the first imaging information and the second imaging information according to the same coordinate system. ¶ [0176], Merely by way of example, the second imaging information include a plurality of MR images of the subject); the second ROI in each of the plurality of second images is relevant to the first ROI in the first image (See Zhang, ¶ [0075], the identification unit 520 may identify at least one ROI associated with the at least one first target ROI in the second imaging information, and designate the identified at least one ROI associated with the at least one first target ROI as the at least one second target ROI);
the report generating device is further configured to generate a human readable report of the target part according to the quantified parameter information corresponding to the second ROI in each of the plurality of second images (See Zhang, ¶ [0076], The report generation unit 530 may generate a report based on at least a part of the first reporting information or the second reporting information. In some embodiments, the diagnostic imaging report may include at least one of an image, an annotation, text, or a video. In some embodiments, the annotation may be associated with an image or one or more video frames of a video. The annotation may include region features (e.g., the first region features and/or the second region features), such as a name, a length, an area, a density, a grayscale, or the like, or any combination thereof. Note: Examiner is interpreting area, length and density as quantified parameter information), wherein the human readable report comprises quantified parameter information of the target part in different dimensions (See Zhang, ¶ [0076], The annotation may include region features (e.g., the first region features and/or the second region features), such as a name, a length, an area, a density, a grayscale, or the like, or any combination thereof. Note: Examiner is interpreting area, length and density as different quantified parameter information).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Leng’s reference to the report generating device is configured to identify a first region of interest (ROI) in the first image or utilize a first ROI manually circled on the first image, and configured to perform a registration for the first image and each of the plurality of second images; the second ROI in each of the plurality of second images is relevant to the first ROI in the first image; the report generating device is further configured to generate a human readable report of the target part according to the quantified parameter information corresponding to the second ROI in each of the plurality of second images, wherein the human readable report comprises quantified parameter information of the target part in different dimensions based on the method of Zhang’s reference. The suggestion/motivation would have been to timely, efficiently and automatically generate medical reports for different imaging modalities (See Zhang, ¶ [0003–0005]).
However, Leng and Zhang fail(s) to teach update the first ROI synchronously in each of the plurality of second images to obtain a second ROI in each of the plurality of second images.
Gooding, working in the same field of endeavor, teaches: update the first ROI synchronously in each of the plurality of second images to obtain a second ROI in each of the plurality of second images (See Gooding, ¶ [0076], The system and method of FIG. 6 may furthermore allow the capture of further changes to the region of interest that a user makes on either the first and/or second medical scan images. The first region representation 660 is then updated in accordance with those further changes. The region of interest displayed on both the first and second medical images can then be updated, based on the updated region representation. ¶ [0120], If all N medical scan images were displayed simultaneously, the normal configuration of the invention would be to update the region of interest on all N images, when a user made changes to it on any of the N images).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Leng’s reference to update the first ROI synchronously in each of the plurality of second images to obtain a second ROI in each of the plurality of second images based on the method of Gooding’s reference. The suggestion/motivation would have been to improve the definition of the region of interest and accurately update the ROI (See Gooding, ¶ [0038–0048]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Zhang and Gooding with Leng to obtain the invention as specified in claim 1.
Regarding claim 2, Leng teaches the system of claim 1, wherein the report generating device is further configured to:
perform the registration for the first image and each of the plurality of second images to obtain a mapping relationship between the first image and each of the plurality of second images (See Leng, ¶ [0031], Optimization in which the best registration parameters are computed via maximization of MI between imaging series. In some examples, as further explained below, the registration parameters that are optimized by data registration module 27 are entries of a transformation matrix (e.g., a 4×4 matrix) that represents the mapping for each pixel within images of the source series for transformation to the target series); and
determine, according to the mapping relationship, an image region in each of the plurality of second images relevant to the first ROI to be the second ROI (See Leng, ¶ [0064], The techniques presented herein select one of the scans as a “target” scan (series) and, independently for each of the other “source” scans (series), generate a 3D mapping function which relates any point in a subregion of interest in the target scan to a point in the source scans which corresponds to the same material point in the body of the patient. Such a map for each of the source fields can then be used to obtain co-registered values of all fields on the mesh of the target field).
Regarding claim 3, Leng in view of Zhang and further in view of Gooding teaches the system of claim 2, wherein the report generating device is further configured to:
[determine first location information of the first ROI in the first image;
determine, according to the mapping relationship, the second location information in each of the plurality of second images relevant to the first location information; and
determine the second ROI in each of the plurality of second images according to the second location information].
However, Leng and Zhang fail(s) to teach determine first location information of the first ROI in the first image; determine, according to the mapping relationship, the second location information in each of the plurality of second images relevant to the first location information; and determine the second ROI in each of the plurality of second images according to the second location information.
Gooding, working in the same field of endeavor, teaches: determine first location information of the first ROI in the first image (See Gooding, ¶ [0075], The first region representation 660 may store information about the geometrical space occupied by the region of interest. Such information may, for example, comprise a mesh of points. These points can be the locations of voxels that make up the region of interest ROIa on the first medical scan image 640. However, the stored information may take other forms, and could comprise all the points of the dataset of the first medical scan image 640 that lie within region of interest ROIa as currently defined);
determine, according to the mapping relationship, the second location information in each of the plurality of second images relevant to the first location information (See Gooding, ¶ [0081], The transformation is achieved by applying to region representation 660 a transformation that is suitable for mapping first medical scan image 640 to second medical scan image 650. In this manner, the original version of the second medical scan image 650 may be viewed, with the region of interest ROIb that is displayed on it corresponding to the region representation 660. The second medical scan image 650 has not been warped as part of image registration); and
determine the second ROI in each of the plurality of second images according to the second location information (See Gooding, ¶ [0081], The transformation is achieved by applying to region representation 660 a transformation that is suitable for mapping first medical scan image 640 to second medical scan image 650. In this manner, the original version of the second medical scan image 650 may be viewed, with the region of interest ROIb that is displayed on it corresponding to the region representation 660. The second medical scan image 650 has not been warped as part of image registration. Note: Examiner is interpreting ROIb as the second ROI).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Leng’s reference to determine first location information of the first ROI in the first image; determine, according to the mapping relationship, the second location information in each of the plurality of second images relevant to the first location information; and determine the second ROI in each of the plurality of second images according to the second location information based on the method of Gooding’s reference. The suggestion/motivation would have been to improve the definition of the region of interest and accurately update the ROI (See Gooding, ¶ [0038–0048]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Gooding with Leng and Zhang to obtain the invention as specified in claim 3.
Regarding claim 4, Leng in view of Zhang further in view of Gooding teaches the system of claim 1, wherein:
each of the plurality of second images is used for depicting the quantified parameter information of the target part in different dimensions (See Leng, ¶ [0032], Image interpretation module 12 receives registered medical imaging data 19 and may determine one or more 2D parameter maps corresponding to the imaged tissue. A 2D parameter map may indicate the value of a parameter at each location of the scanned tissue. For instance, image interpretation module 12 may generate a parameter map for one or more of an apparent T2 (T2) parameter, an apparent diffusion coefficient (ADC) parameter, pharmacokinetic parameters K.sup.Trans, k.sub.ep, and/or an area under the gadolinium concentration time curve over 90 s (AUGC90) parameter. Note: The T2, ADC and pharmacokinetic are being interpreted as quantified parameter information);
[the report generating device is further configured to generate the human readable report of the target part based on the first image, each of the plurality of second images, and the quantified parameter information corresponding to each of the plurality of second ROI].
However, Leng and Gooding fail(s) to teach the report generating device is further configured to generate the human readable report of the target part based on the first image, each of the plurality of second images, and the quantified parameter information corresponding to each of the plurality of second ROI.
Zhang, working in the same field of endeavor, teaches: the report generating device is further configured to generate the human readable report of the target part based on the first image, each of the plurality of second images, and the quantified parameter information corresponding to each of the plurality of second ROI (See Zhang, ¶ [0076], The report generation unit 530 may generate a report based on at least a part of the first reporting information or the second reporting information. In some embodiments, the diagnostic imaging report may include at least one of an image, an annotation, text, or a video. In some embodiments, the annotation may be associated with an image or one or more video frames of a video. The annotation may include region features (e.g., the first region features and/or the second region features), such as a name, a length, an area, a density, a grayscale, or the like, or any combination thereof. Note: Examiner is interpreting area, length and density as quantified parameter information).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Leng’s reference the report generating device is further configured to generate the human readable report of the target part based on the first image, each of the plurality of second images, and the quantified parameter information corresponding to each of the plurality of second ROI based on the method of Zhang’s reference. The suggestion/motivation would have been to timely, efficiently and automatically generate medical reports for different imaging modalities (See Zhang, ¶ [0003–0005]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Zhang with Leng and Gooding to obtain the invention as specified in claim 4.
Regarding claim 10, Leng in view of Zhang and further in view of Gooding teaches the system of claim 1, wherein the report generating device is further configured to: [determine a region identifying model corresponding to the target part; and
input the first image into the region identifying model corresponding to the target part to obtain the first ROI in the first image].
However, Leng and Gooding fail(s) to teach determine a region identifying model corresponding to the target part; and input the first image into the region identifying model corresponding to the target part to obtain the first ROI in the first image.
Zhang, working in the same field of endeavor, teaches: determine a region identifying model corresponding to the target part (See Zhang, ¶ [0098], In some embodiments, the processing module 420 may identify a first target ROI based on first imaging information automatically using a first target ROI determination model); and
input the first image into the region identifying model corresponding to the target part to obtain the first ROI in the first image (See Zhang, ¶ [0098], In some embodiments, the processing module 420 may identify a first target ROI based on first imaging information automatically using a first target ROI determination model).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Leng’s reference to determine a region identifying model corresponding to the target part; and input the first image into the region identifying model corresponding to the target part to obtain the first ROI in the first image based on the method of Zhang’s reference. The suggestion/motivation would have been to provide an accurate and comprehensive media imaging report (See Zhang, ¶ [0004–0005]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Zhang with Leng and Gooding to obtain the invention as specified in claim 10.
Regarding claim 11, claim 11 is rejected the same as claim 1 and the arguments similar to that presented above for claim 1 are equally applicable to the claim 11, and all of the other limitations similar to claim 1 are not repeated herein, but incorporated by reference.
Regarding claim 12, Leng in view of Zhang further in view of Gooding teaches the method of claim 11, wherein the performing the registration for the first image and each of the plurality of second images (See Leng, ¶ [0031], Optimization in which the best registration parameters are computed via maximization of MI between imaging series. In some examples, as further explained below, the registration parameters that are optimized by data registration module 27 are entries of a transformation matrix (e.g., a 4×4 matrix) that represents the mapping for each pixel within images of the source series for transformation to the target series) to [update the first ROI synchronously in each of the plurality of second images to obtain the second ROI in each of the plurality of second images] comprises:
performing the registration for the first image and each of the plurality of second images to obtain a mapping relationship between the first image and each of the plurality of second images (See Leng, ¶ [0031], Optimization in which the best registration parameters are computed via maximization of MI between imaging series. In some examples, as further explained below, the registration parameters that are optimized by data registration module 27 are entries of a transformation matrix (e.g., a 4×4 matrix) that represents the mapping for each pixel within images of the source series for transformation to the target series); and
determining, according to the mapping relationship, an image region in each of the plurality of second images relevant to the first ROI to be the second ROI (See Leng, ¶ [0064], The techniques presented herein select one of the scans as a “target” scan (series) and, independently for each of the other “source” scans (series), generate a 3D mapping function which relates any point in a subregion of interest in the target scan to a point in the source scans which corresponds to the same material point in the body of the patient. Such a map for each of the source fields can then be used to obtain co-registered values of all fields on the mesh of the target field).
However, Leng and Zhang fail(s) to teach update the first ROI synchronously in each of the plurality of second images to obtain the second ROI in each of the plurality of second images.
Gooding, working in the same field of endeavor, teaches: update the first ROI synchronously in each of the plurality of second images to obtain the second ROI in each of the plurality of second images (See Gooding, ¶ [0076], The system and method of FIG. 6 may furthermore allow the capture of further changes to the region of interest that a user makes on either the first and/or second medical scan images. The first region representation 660 is then updated in accordance with those further changes. The region of interest displayed on both the first and second medical images can then be updated, based on the updated region representation. ¶ [0120], If all N medical scan images were displayed simultaneously, the normal configuration of the invention would be to update the region of interest on all N images, when a user made changes to it on any of the N images).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Leng’s reference to update the first ROI synchronously in each of the plurality of second images to obtain the second ROI in each of the plurality of second images based on the method of Gooding’s reference. The suggestion/motivation would have been to improve the definition of the region of interest and accurately update the ROI (See Gooding, ¶ [0038–0048]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Gooding with Leng and Zhang to obtain the invention as specified in claim 12.
Regarding claim 13, claim 13 is rejected the same as claim 3 and the arguments similar to that presented above for claim 3 are equally applicable to the claim 13, and all of the other limitations similar to claim 3 are not repeated herein, but incorporated by reference.
Regarding claim 14, claim 14 is rejected the same as claim 4 and the arguments similar to that presented above for claim 4 are equally applicable to the claim 14, and all of the other limitations similar to claim 4 are not repeated herein, but incorporated by reference.
Regarding claim 18, Leng teaches a computer apparatus, comprising a memory and a processor, wherein, a computer program is stored in the memory, and the processor, when executing the computer program, performs steps of the method of claim 11 (See Leng, [FIG. 2], 510 Processor, 530 Memory).
Regarding claim 19, Leng teaches a non-transitory computer readable storage medium, having a computer program stored thereon, wherein, the computer program, when executed by a processor, causes the processor to perform steps of the method of claim 11 (See Leng, [FIG. 2], 510 Processor, 530 Memory).
Regarding claim 21, Leng teaches a medical image processing system, comprising a medical imaging device and a report generating device, wherein:
the medical imaging device is configured to acquire a first image and a second image of a target part (See Leng, ¶ [0027], As one example, medical imaging data 18 may represent various two-dimensional (2D) images of a prostate gland of patient 8. Each 2D image may be a different plane of the scanned tissue. That is, the medical imaging device that generates medical imaging data 18 may take multiple 2D scans, each at a different point along a third dimension. In this way, the composite of medical imaging data 18 may, in some examples, be a series of planes (e.g., “slices”) of the scanned tissue), and [transmit the first image and the second image to the report generating device]; the first image is used for depicting an anatomy structure of the target part, and the second image is used for depicting quantified parameter information of the target part (See Leng, ¶ [0032], Image interpretation module 12 receives registered medical imaging data 19 and may determine one or more 2D parameter maps corresponding to the imaged tissue. A 2D parameter map may indicate the value of a parameter at each location of the scanned tissue. For instance, image interpretation module 12 may generate a parameter map for one or more of an apparent T2 (T2) parameter, an apparent diffusion coefficient (ADC) parameter, pharmacokinetic parameters K.sup.Trans, k.sub.ep, and/or an area under the gadolinium concentration time curve over 90 s (AUGC90) parameter. See also [FIG. 5A and 5B]. Note: The T2 anatomic image is being interpreted as the structure, and the ADC and pharmacokinetic are being interpreted as quantified parameter information);
[the report generating device is configured to identify a first region of interest (ROI) in the first image or utilize a first ROI manually circled on the first image, and configured to perform a registration for the first image and the second image to update the first ROI synchronously in the second image to obtain a second ROI in the second image; the second ROI in the second image is relevant to the first ROI in the first image;
the report generating device is further configured to generate a human readable report of the target part according to the quantified parameter information corresponding to the second ROI in the second image];
wherein the first image and the second image are obtained by exciting the target part using different magnetic resonance imaging sequences (See Leng, ¶ [0027], In the example of FIG. 1, data registration module 27 is configured to receive and process medical imaging data 18, which typically takes the form of magnetic resonance imaging (MRI) data or, in some examples, multiparametric magnetic resonance imaging (mpMRI) data. See [FIG. 5A and 5B]. See also ¶ [0102] and Table 1, Imaging sequence parameters use for capturing the multiparametric MRI are shown in Table 1. Note: multiparametric MRI data is taking multiple parametric images such as T2 and DWI, ADC or DCE images as shown in Table 1. The T2 anatomic image is being interpreted as the structural qualitative protocol, and the ADC, pharmacokinetic, DCE and DWI are being interpreted as quantitative protocol); magnetic resonance imaging sequences corresponding to the first image are obtained through a structural qualitative protocol; and magnetic resonance imaging sequences corresponding to the second image are obtained through a quantitative protocol (See Leng, ¶ [0032], Image interpretation module 12 receives registered medical imaging data 19 and may determine one or more 2D parameter maps corresponding to the imaged tissue. A 2D parameter map may indicate the value of a parameter at each location of the scanned tissue. For instance, image interpretation module 12 may generate a parameter map for one or more of an apparent T2 (T2) parameter, an apparent diffusion coefficient (ADC) parameter, pharmacokinetic parameters K.sup.Trans, k.sub.ep, and/or an area under the gadolinium concentration time curve over 90 s (AUGC90) parameter. ¶ [0027], In the example of FIG. 1, data registration module 27 is configured to receive and process medical imaging data 18, which typically takes the form of magnetic resonance imaging (MRI) data or, in some examples, multiparametric magnetic resonance imaging (mpMRI) data. See also [FIG. 5A and 5B]. Note: multiparametric MRI data is taking multiple parametric images such as T2 and DWI, ADC or DCE images. The T2 anatomic image is being interpreted as the structural qualitative protocol, and the ADC and pharmacokinetic are being interpreted as quantitative protocol).
However, Leng fail(s) to teach transmit the first image and the plurality of second images to the report generating device; the report generating device is configured to identify a first region of interest (ROI) in the first image or utilize a first ROI manually circled on the first image, and configured to perform a registration for the first image and the second image to update the first ROI synchronously in the second image to obtain a second ROI in the second image; the second ROI in the second image is relevant to the first ROI in the first image; the report generating device is further configured to generate a human readable report of the target part according to the quantified parameter information corresponding to the second ROI in the second image.
Zhang, working in the same field of endeavor, teaches: transmit the first image and the plurality of second images to the report generating device (See Zhang, ¶ [0065], The obtaining module 410 may obtain data and/or information. In some embodiments, the obtaining module 410 may obtain imaging information from a multi-modality imaging device. The imaging information may be acquired from a scan of a subject using the multi-modality imaging device. The imaging information may include an image (e.g., a two-dimensional (2D) image, a three-dimensional (3D) image, etc.), a video (e.g., a 2D video, a 3D video, etc.), image data (e.g., image data corresponding to an image or a video), or the like. ¶ [0066], The processing module 420 may process data and/or information, and generate a diagnostic imaging report based on the processed data);
the report generating device is configured to identify a first region of interest (ROI) in the first image (See Zhang, ¶ [0073], The identification unit 520 may identify one or more ROIs with respect to the first imaging information and/or the second imaging information. In some embodiments, the identification unit 520 may identify at least one first target ROI based on the first imaging information, and determine first reporting information corresponding to the at least one first target ROI. In some embodiments, the first reporting information may include at least one of an image, text, a video, or an annotation) or utilize a first ROI manually circled on the first image (See Zhang, ¶ [0073], In some embodiments, the obtaining unit 510 may receive a region selection instruction from a user. The region selection instruction may direct the identification unit 520 to select at least one first target ROI from the at least two candidate ROIs), and configured to perform a registration for the first image and the second image (See Zhang, ¶ [0075], The identification unit 520 may perform the image fusion or image registration between the first imaging information and the second imaging information according to the same coordinate system. ¶ [0176], Merely by way of example, the second imaging information include a plurality of MR images of the subject); the second ROI in the second image is relevant to the first ROI in the first image (See Zhang, ¶ [0075], the identification unit 520 may identify at least one ROI associated with the at least one first target ROI in the second imaging information, and designate the identified at least one ROI associated with the at least one first target ROI as the at least one second target ROI);
the report generating device is further configured to generate a human readable report of the target part according to the quantified parameter information corresponding to the second ROI in the second image (See Zhang, ¶ [0076], The report generation unit 530 may generate a report based on at least a part of the first reporting information or the second reporting information. In some embodiments, the diagnostic imaging report may include at least one of an image, an annotation, text, or a video. In some embodiments, the annotation may be associated with an image or one or more video frames of a video. The annotation may include region features (e.g., the first region features and/or the second region features), such as a name, a length, an area, a density, a grayscale, or the like, or any combination thereof. Note: Examiner is interpreting area, length and density as quantified parameter information).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Leng’s reference transmit the first image and the plurality of second images to the report generating device; the report generating device is configured to identify a first region of interest (ROI) in the first image or utilize a first ROI manually circled on the first image, and configured to perform a registration for the first image and the second image; the second ROI in the second image is relevant to the first ROI in the first image; the report generating device is further configured to generate a human readable report of the target part according to the quantified parameter information corresponding to the second ROI in the second image based on the method of Zhang’s reference. The suggestion/motivation would have been to timely, efficiently and automatically generate medical reports for different imaging modalities (See Zhang, ¶ [0003–0005]).
However, Leng and Zhang fail(s) to teach update the first ROI synchronously in the second image to obtain a second ROI in the second image.
Gooding, working in the same field of endeavor, teaches: update the first ROI synchronously in the second image to obtain a second ROI in the second image (See Gooding, ¶ [0076], The system and method of FIG. 6 may furthermore allow the capture of further changes to the region of interest that a user makes on either the first and/or second medical scan images. The first region representation 660 is then updated in accordance with those further changes. The region of interest displayed on both the first and second medical images can then be updated, based on the updated region representation. ¶ [0120], If all N medical scan images were displayed simultaneously, the normal configuration of the invention would be to update the region of interest on all N images, when a user made changes to it on any of the N images).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Leng’s reference to update the first ROI synchronously in the second image to obtain a second ROI in the second image based on the method of Gooding’s reference. The suggestion/motivation would have been to improve the definition of the region of interest and accurately update the ROI (See Gooding, ¶ [0038–0048]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Zhang and Gooding with Leng to obtain the invention as specified in claim 21.
Claim(s) 5 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Leng et al. (US 20200214619 A1, hereafter, “Leng”) in view of Zhang et al. (US 20200303049 A1, hereafter, "Zhang”) and further in view of Gooding et al. (US 20140247284 A1, hereafter, “Gooding”) and further in view of Wang et al. (CN 110021025 A, hereafter, "Wang").
Regarding claim 5, Leng in view of Zhang further in view of Gooding teaches the system of claim 4, [wherein the report generating device is further configured to: acquire an information reference value corresponding to each quantified parameter information;
generate an information abnormality marker in a case that the quantified parameter information does not conform to the information reference value; and
generate the human readable report according to the first image, each of the plurality of second image, each quantified parameter information, each information reference value, and each information abnormality marker].
However, Leng and Gooding fail(s) to teach wherein the report generating device is further configured to: acquire an information reference value corresponding to each quantified parameter information; generate an information abnormality marker in a case that the quantified parameter information does not conform to the information reference value; each information reference value, and each information abnormality marker.
Wang, working in the same field of endeavor, teaches: wherein the report generating device is further configured to: acquire an information reference value corresponding to each quantified parameter information (See Wang, ¶ [0132], Figure 13 is a schematic diagram of the matching results displayed in text form provided by an embodiment of the present invention, Figure 14 is a schematic diagram of the matching results displayed in tabular form provided by an embodiment of the present invention. [Figure 14], Historical, Current, Result. Note: Examiner is interpreting the Historical as the reference);
generate an information abnormality marker in a case that the quantified parameter information does not conform to the information reference value (See Wang, [Figure 14], Historical, Current, Result. Note: Examiner is interpreting the Historical as the reference, the current as the quantified parameter information and the result marker as the abnormality marker); and
each information reference value, and each information abnormality marker (See Wang, [Figure 14], Historical, Current, Result. Note: Examiner is interpreting the Historical as the reference, the current as the quantified parameter information and the result marker as the abnormality marker).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Leng’s reference wherein the report generating device is further configured to: acquire an information reference value corresponding to each quantified parameter information; generate an information abnormality marker in a case that the quantified parameter information does not conform to the information reference value; each information reference value, and each information abnormality marker based on the method of Wang’s reference. The suggestion/motivation would have been more accurately track and match regions of interest over time (See Wang, ¶ [0004, 0041]).
However, Leng, Gooding and Wang fail(s) to teach generate the human readable report according to the first image, each of the plurality of second image, each quantified parameter information.
Zhang, working in the same field of endeavor, teaches: generate the human readable report according to the first image, each of the plurality of second image, each quantified parameter information (See Zhang, ¶ [0076], The report generation unit 530 may generate a report based on at least a part of the first reporting information or the second reporting information. In some embodiments, the diagnostic imaging report may include at least one of an image, an annotation, text, or a video. In some embodiments, the annotation may be associated with an image or one or more video frames of a video. The annotation may include region features (e.g., the first region features and/or the second region features), such as a name, a length, an area, a density, a grayscale, or the like, or any combination thereof. Note: Examiner is interpreting area, length and density as quantified parameter information).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Zhang’s reference generate the human readable report according to the first image, each of the plurality of second image, each quantified parameter information based on the method of Zhang’s reference. The suggestion/motivation would have been to timely, efficiently and automatically generate medical reports for different imaging modalities (See Zhang, ¶ [0003–0005]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Wang and Zhang with Leng and Gooding to obtain the invention as specified in claim 5.
Regarding claim 15, claim 15 is rejected the same as claim 5 and the arguments similar to that presented above for claim 5 are equally applicable to the claim 15, and all of the other limitations similar to claim 5 are not repeated herein, but incorporated by reference.
Claim(s) 6 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Leng et al. (US 20200214619 A1, hereafter, “Leng”) in view of Zhang et al. (US 20200303049 A1, hereafter, "Zhang”) further in view of Gooding et al. (US 20140247284 A1, hereafter, “Gooding”) further in view of Wang et al. (CN 110021025 A, hereafter, "Wang") and further in view of Moriya (US 2011/0075913 A1, hereafter, "Moriya").
Regarding claim 6, Leng in view of Zhang further in view of Gooding and further in view of Wang teaches the system of claim 5, [wherein the report generating device is further configured to present a display window for displaying second image in response to a triggering operation for state information of the target part in the human readable report; and
a target second image corresponding to the state information of the target part is shown in the display window for displaying second image].
However, Leng, Zhang, Gooding and Wang fail(s) to teach wherein the report generating device is further configured to present a display window for displaying second image in response to a triggering operation for state information of the target part in the human readable report; and a target second image corresponding to the state information of the target part is shown in the display window for displaying second image.
Moriya, working in the same field of endeavor, teaches: wherein the report generating device is further configured to present a display window for displaying second image in response to a triggering operation for state information of the target part in the human readable report (See Moriya, ¶ [0052], Radiology report generation unit 30 may generate a radiology report in which a character string is related by hyperlink to a medical image, position information of a lesion area of the medical image, or a character string of another radiology report. The attending doctor or the like may click on the character string (link character) of the radiology report on the screen to display a medical image or the like related to the character string on the display); and
a target second image corresponding to the state information of the target part is shown in the display window for displaying second image (See Moriya, ¶ [0052], Radiology report generation unit 30 may generate a radiology report in which a character string is related by hyperlink to a medical image, position information of a lesion area of the medical image, or a character string of another radiology report. The attending doctor or the like may click on the character string (link character) of the radiology report on the screen to display a medical image or the like related to the character string on the display).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Leng’s reference wherein the report generating device is further configured to present a display window for displaying second image in response to a triggering operation for state information of the target part in the human readable report; and a target second image corresponding to the state information of the target part is shown in the display window for displaying second image based on the method of Moriya’s reference. The suggestion/motivation would have been to improve the lesion extraction performance (See Moriya, ¶ [0010]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Moriya with Leng, Zhang, Gooding and Wang to obtain the invention as specified in claim 6.
Regarding claim 16, claim 16 is rejected the same as claim 6 and the arguments similar to that presented above for claim 6 are equally applicable to the claim 16, and all of the other limitations similar to claim 6 are not repeated herein, but incorporated by reference.
Claim(s) 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Leng et al. (US 20200214619 A1, hereafter, “Leng”) in view of Zhang et al. (US 20200303049 A1, hereafter, "Zhang”) further in view of Gooding et al. (US 20140247284 A1, hereafter, “Gooding”) further in view of Wang et al. (CN 110021025 A, hereafter, "Wang") further in view of Moriya (US 2011/0075913 A1, hereafter, "Moriya") and further in view of Parsey et al. (US 2011/0160543 A1, hereafter, "Parsey").
Regarding claim 7, Leng in view of Zhang further in view of Gooding further in view of Wang and further in view of Moriya teaches the system of claim 6, wherein the report generating device is further configured to:
determine a third ROI in the target second image in response to a region selection operation for the target second image in the display window for displaying second image (See Leng, ¶ [0028], Automated or manual determination of the volume of interest (VOI) on which registration parameters are optimized. The VOI may, in some examples, be determined from radiologists' annotation of the prostate capsule. ¶ [0104], FIGS. 5A-5B show the results plus registered parametric maps for a representative case. In particular, FIG. 5A is a set of images in which regions of interest (ROIs) drawn on an axial slice of the T2w anatomic series and propagated to both unregistered and registered source volumes. In this case, co-localization of both the anatomic landmark (yellow ROI) and the region suspicious for cancer (blue ROI) is clearly superior after registration with the proposed methods. Note: Examiner is interpreting the yellow ROI and the blue ROI co localized on each image as the third and fourth ROI);
determine a fourth ROI relevant to the third ROI in each of the plurality of second images other than in the target second image (See Leng, ¶ [0104], FIGS. 5A-5B show the results plus registered parametric maps for a representative case. In particular, FIG. 5A is a set of images in which regions of interest (ROIs) drawn on an axial slice of the T2w anatomic series and propagated to both unregistered and registered source volumes. In this case, co-localization of both the anatomic landmark (yellow ROI) and the region suspicious for cancer (blue ROI) is clearly superior after registration with the proposed methods. Note: Examiner is interpreting the yellow ROI and the blue ROI co localized on each image as the third and fourth ROI); and
[update the human readable report according to quantified parameter information corresponding to the third ROI and quantified parameter information corresponding to the fourth ROI].
However, Leng, Zhang, Gooding, Wang and Moriya fail(s) to teach update the human readable report according to quantified parameter information corresponding to the third ROI and quantified parameter information corresponding to the fourth ROI.
Parsey, working in the same field of endeavor, teaches: update the human readable report according to quantified parameter information corresponding to the third ROI and quantified parameter information corresponding to the fourth ROI (See Parsey, ¶ [0168], The PET is used as a measure of the protein and the MRI is used to identify anatomical structures by manual or processor-driven determination of regions of interest (ROIs). The PET is then spatially aligned to the MRI after which the PET can be used to quantify the levels of a protein in identified anatomical structures. See also [FIG. 4D], FIG. 4D shows the final cortical BP.sub.ND measure. Note: Examiner is interpreting the BP as the human readable quantified parameter information).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Leng’s reference update the human readable report according to quantified parameter information corresponding to the third ROI and quantified parameter information corresponding to the fourth ROI based on the method of Parsey’s reference. The suggestion/motivation would have been to provide PET based diagnosing for improved treatment decisions (See Parsey, ¶ [0005–0007]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Parsey with Leng, Zhang, Gooding, Wang and Moriya to obtain the invention as specified in claim 7.
Regarding claim 17, claim 17 is rejected the same as claim 7 and the arguments similar to that presented above for claim 7 are equally applicable to the claim 17, and all of the other limitations similar to claim 7 are not repeated herein, but incorporated by reference.
Claim(s) 8 is rejected under 35 U.S.C. 103 as being unpatentable over Leng et al. (US 20200214619 A1, hereafter, “Leng”) in view of Zhang et al. (US 20200303049 A1, hereafter, "Zhang”) further in view of Gooding et al. (US 20140247284 A1, hereafter, “Gooding”) further in view of Wang et al. (CN 110021025 A, hereafter, "Wang") further in view of Hou et al. (US 2007/0274585 A1, hereafter, "Hou").
Regarding claim 8, Leng in view of Zhang further in view of Gooding and further in view of Wang teaches the system of claim 5, wherein the report generating device is further configured to: [present an enlarged second image in the human readable report in response to a first triggering operation for each of the plurality of second images in the human readable report;
or reduce the enlarged second image in response to a second triggering operation for the enlarged second image].
However, Leng, Zhang, Gooding and Wang fail(s) to teach present an enlarged second image in the human readable report in response to a first triggering operation for each of the plurality of second images in the human readable report; or reduce the enlarged second image in response to a second triggering operation for the enlarged second image.
Hou, working in the same field of endeavor, teaches: present an enlarged second image in the human readable report in response to a first triggering operation for each of the plurality of second images in the human readable report (See Hou, ¶ [0068], As other display alternatives, single image enlargement is also available, as shown in the example of FIG. 4, where display monitors 54a and 54b each show the same view on the full screen, one for each of current and prior exams. Single image enlargement may be performed, for example, upon verbal command or by clicking on the image displayed at navigation display 52);
or reduce the enlarged second image in response to a second triggering operation for the enlarged second image (See Hou, ¶ [0068], This mode can be toggled back to the original display mode or another image can be selected using navigation display 52).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Leng’s reference present an enlarged second image in the human readable report in response to a first triggering operation for each of the plurality of second images in the human readable report; or reduce the enlarged second image in response to a second triggering operation for the enlarged second image based on the method of Hou’s reference. The suggestion/motivation would have been to improve the effectiveness of screening and diagnosis (See Hou, ¶ [0023]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Hou with Leng, Zhang, Gooding and Wang to obtain the invention as specified in claim 8.
Claim(s) 9 is rejected under 35 U.S.C. 103 as being unpatentable over Leng et al. (US 20200214619 A1, hereafter, “Leng”) in view of Zhang et al. (US 20200303049 A1, hereafter, "Zhang”) further in view of Gooding et al. (US 20140247284 A1, hereafter, “Gooding”) further in view of Wang et al. (CN 110021025 A, hereafter, "Wang") and further in view of He et al. (WO 2021/109043 A1, hereafter, "He").
Regarding claim 9, Leng in view of Zhang further in view of Gooding and further in view of Wang teaches the system of claim 5, [wherein the report generating device is further configured to delete quantified parameter information corresponding to a target second ROI in the human readable report in response to a region deletion operation for the target second ROI in each of the plurality of second image in the human readable report].
However, Leng, Zhang, Gooding and Wang fail(s) to teach wherein the report generating device is further configured to delete quantified parameter information corresponding to a target second ROI in the human readable report in response to a region deletion operation for the target second ROI in each of the plurality of second image in the human readable report.
He, working in the same field of endeavor, teaches: wherein the report generating device is further configured to delete quantified parameter information corresponding to a target second ROI in the human readable report in response to a region deletion operation for the target second ROI in each of the plurality of second image in the human readable report (See He, [Pg. 37, ln. 30-31], In step 720, the MRI system 10 conducts image preprocessing to remove the regions of non-interests in radiological images. [Pg. 38, ln. 5-7, 13-14], In step 740, the MRI system 10 classifies cell types of the cells in the radiological images using a classifier of the deep learning model and quantifying the number of classified cells, ..., Finally, another independent set of images is used to test the model and report final statistical results).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Leng’s reference wherein the report generating device is further configured to delete quantified parameter information corresponding to a target second ROI in the human readable report in response to a region deletion operation for the target second ROI in each of the plurality of second image in the human readable report based on the method of He’s reference. The suggestion/motivation would have been to more accurately and quickly respond to brain tumors (See He, [Pg. 1, ln. 10–13 – Pg. 6, ln. 1–5]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine He with Leng, Zhang, Gooding and Wang to obtain the invention as specified in claim 9.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Choi et al. (US 20140200433 A1) teaches an apparatus for estimating a malignant tumor includes: a segmentor configured to segment a first medical image of an object into a first ROI including a mass and a second medical image of the object into a second ROI including a mass; an interest region determiner configured to acquire a first matched ROI and a second matched ROI, which is matched to the first matched ROI based on location information of the first ROI and the second ROI, respectively; a feature extractor configured to extract a similar feature indicating a degree of similarity between the first matched ROI and the second matched ROI, from the first matched ROI and the second matched ROI; and a classifier configured to generate malignant tumor information indicating whether the mass included in the first matched ROI and the second matched ROI is the malignant tumor, based on the extracted similar feature.
Schoenmeyer et al. (US 20150287194 A1) teaches the coregistration of digital images of tissue slices is improved by updating landmarks based on the manual outlining of regions of interest on the images. A first image of a first slice is coarsely coregistered with a second image of a second slice using a first landmark on the first image and a second landmark on the second image. A user manually outlines a first region of interest on the first image. The outline is positioned over a second region of interest on the second image using the second landmark. The user manually moves a contour point of the outline on the second image to form a corrected outline. The second landmark is moved based on how the contour point was manually moved so that the first and second images are more finely coregistered after the second landmark is moved. Each state of corrected contour points and landmarks is saved.
Griswold et al. (US 10667718 B2) teaches sampling is performed with t and/or E varying in a non-constant way. The NMR apparatus may also include a signal logic that produces an NMR signal evolution from the NMR signals and a characterization logic that characterizes a tissue in the object as a result of comparing acquired signals to reference signals. Example embodiments facilitate distinguishing prostate cancer tissue from normal peripheral zone tissue based on quantitative data acquired using NMR fingerprinting in combination with apparent diffusion co-efficient (ADC) values or perfusion values acquired using DWI-MRI or DCE-MRI.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DION J SATCHER whose telephone number is (703)756-5849. The examiner can normally be reached Monday - Thursday 5:30 am - 2:30 pm, Friday 5:30 am - 9:30 am PST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Henok Shiferaw can be reached at (571) 272-4637. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DION J SATCHER/ Patent Examiner, Art Unit 2676
/Henok Shiferaw/ Supervisory Patent Examiner, Art Unit 2676
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