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 .
Notice to Applications
This communication is in response to the Application filed on August 30, 2024.
Claims 1-20 are pending.
Information Disclosure Statement
The information disclosure statement(s) (IDS(s)) submitted on December 02, 2024 and June 17, 2025 are in compliance with the provisions of 27 CFR 1.97. Accordingly, the information disclosure statements are being considered and attached by the examiner.
Priority
Acknowledgement is made of applicant’s claim for foreign priority under 35 U.S.C. 119(a)-(d).
The certified copies have been filed as Application No. JP2022-035379, filed on March 08, 2022.
Specification
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.
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 nonobviousness.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable of Morita et al., US 20210166443 A1, (hereinafter “Morita”) in view of Sendai et al., US 20090118614 A1, (hereinafter “Sendai”).
Regarding claim 1, Morita teaches an image processing apparatus comprising:
at least one processor ([0167] “The various processors include not only the above-described CPU, which is a general-purpose processor that executes software (program) and functions as various processing units, but also a programmable logic device (PLD) that is a processor whose circuit configuration can be changed after manufacture, such as a field programmable gate array (FPGA), and a dedicated electric circuit that is a processor having a circuit configuration that is designed for exclusive use in order to execute specific processing, such as an application specific integrated circuit (ASIC).”),
wherein the at least one processor is configured to:
acquire a plurality of projection images that are generated by performing, by an imaging apparatus, tomosynthesis imaging by relatively moving a radiation source with respect to a detection surface of a detection unit and irradiating a subject with radiation at a plurality of radiation source positions due to movement of the radiation source, the plurality of projection images corresponding to the plurality of radiation source positions ([0009] “A tomographic image generating apparatus according to an aspect of the present disclosure comprises an image acquisition unit that acquires a plurality of projection images corresponding to a plurality of radiation source positions, the plurality of projection images being generated by causing an imaging apparatus to perform tomosynthesis imaging in which a radiation source is moved relative to a detection surface of a detection unit in order to emit radiation to a subject at the plurality of radiation source positions according to movement of the radiation source,”);
derive a plurality of feature-structure projection images by extracting a specific structure from the plurality of projection images ([0087] “The projection unit 34 projects the plurality of projection images Gi on the corresponding tomographic plane which is the tomographic plane corresponding to the tomographic image in which the feature point F1 is detected, based on the positional relationship between the radiation source position and the radiation detector 15 in a case of imaging the plurality of projection images Gi.” wherein feature-structure projection images are detected feature points on projection images and a specific structure is a feature point);
derive a plurality of feature-structure tomographic images respectively for a plurality of tomographic planes of the subject by reconstructing the plurality of feature-structure projection images ([0022] “In the tomographic image generating apparatus according to the aspect of the present disclosure, the reconstruction unit may reconstruct all or a part of the plurality of projection images while correcting the positional shift amount to generate a plurality of the corrected tomographic images on the plurality of tomographic planes of the subject as a plurality of new tomographic images,” wherein feature-structure tomographic images are new tomographic images);
detect at least one feature ([0022] “the feature point detecting unit may detect the feature point from the plurality of new tomographic images,”); and
derive a corrected tomographic image for at least one tomographic plane of the subject by correcting misregistration between the plurality of projection images due to a body movement of the subject by using, as a reference, the feature structure in a corresponding tomographic plane corresponding to the feature-structure tomographic image from which the feature structure is detected, and reconstructing the plurality of projection images ([0030] “deriving a positional shift amount between the plurality of projection images based on body movement of the subject with the feature point as a reference on a corresponding tomographic plane corresponding to the tomographic image in which the feature point is detected, and reconstructing the plurality of projection images by correcting the positional shift amount to generate a corrected tomographic image on at least one tomographic plane of the subject.” wherein misregistration is positional shift).
Morita does not specifically disclose a feature structure.
However, Sendai teaches a feature structure ([0063] “The determination of breast type is performed in the following manner. First, the breast type determining part 31a extracts a region, where the breast is shown, from the X-ray image represented by the X-ray image data. For example, a pixel having a value of X-ray image data that is equal to or larger than a predetermined value and has a difference between values of X-ray image data in surrounding pixels and itself equal to or larger than a predetermined value is determined to be a boundary of the breast region.” wherein a feature structure is a breast region).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to detect a feature structure of Sendai in the tomosynthesis imaging apparatus of Morita to more accurately image the breast to discriminate between benign and malignant breast masses.
Regarding claim 2, Morita in view of Sendai teaches the image processing apparatus according to claim 1,
wherein the specific structure is at least one of a line structure or a point structure (Morita - [0087] “The projection unit 34 projects the plurality of projection images Gi on the corresponding tomographic plane which is the tomographic plane corresponding to the tomographic image in which the feature point F1 is detected, based on the positional relationship between the radiation source position and the radiation detector 15 in a case of imaging the plurality of projection images Gi.” wherein a specific structure is a feature point).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 3, Morita in view of Sendai teaches the image processing apparatus according to claim 2,
wherein the at least one processor is configured to extract at least one of the line structure or the point structure based on a concentration degree of a gradient vector representing a gradient of pixel values in the projection image (Morita - [0167] “The various processors include not only the above-described CPU, which is a general-purpose processor that executes software (program) and functions as various processing units, but also a programmable logic device (PLD) that is a processor whose circuit configuration can be changed after manufacture, such as a field programmable gate array (FPGA), and a dedicated electric circuit that is a processor having a circuit configuration that is designed for exclusive use in order to execute specific processing, such as an application specific integrated circuit (ASIC).”) (Morita - [0087] “The projection unit 34 projects the plurality of projection images Gi on the corresponding tomographic plane which is the tomographic plane corresponding to the tomographic image in which the feature point F1 is detected, based on the positional relationship between the radiation source position and the radiation detector 15 in a case of imaging the plurality of projection images Gi.” wherein a specific structure is a feature point) (Sendai - [0078] “Generally, in an X-ray image, the shadow of a tumor mass is slightly lower in density (i.e., higher in brightness) than the surroundings, and the gradient vector in an arbitrary pixel is directed toward the center of the tumor mass shadow. Accordingly, the CAD processing part 31b calculates the density gradient in the X-ray image and obtains the degree of concentration of gradient vectors, and thereby, extracts a candidate region of abnormal shadow. The degree of concentration of gradient vectors is evaluated by using an iris filter, for example.”).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 4, Morita in view of Sendai teaches the image processing apparatus according to claim 1,
wherein the at least one processor is configured to:
derive, in the corresponding tomographic plane, a misregistration amount between the plurality of projection images due to the body movement of the subject by using, as a reference, the feature structure; and derive the corrected tomographic image by correcting the misregistration amount and reconstructing the plurality of projection images (Morita - [0030] “deriving a positional shift amount between the plurality of projection images based on body movement of the subject with the feature point as a reference on a corresponding tomographic plane corresponding to the tomographic image in which the feature point is detected, and reconstructing the plurality of projection images by correcting the positional shift amount to generate a corrected tomographic image on at least one tomographic plane of the subject.” wherein a misregistration amount is a positional shift amount) (Sendai - [0063] “The determination of breast type is performed in the following manner. First, the breast type determining part 31a extracts a region, where the breast is shown, from the X-ray image represented by the X-ray image data. For example, a pixel having a value of X-ray image data that is equal to or larger than a predetermined value and has a difference between values of X-ray image data in surrounding pixels and itself equal to or larger than a predetermined value is determined to be a boundary of the breast region.” wherein a feature structure is a breast region).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 5, Morita in view of Sendai teaches the image processing apparatus according to claim 4,
wherein the at least one processor is configured to:
detect a plurality of feature structures from the plurality of the feature-structure tomographic images; determine whether or not the corresponding tomographic plane corresponding to the feature-structure tomographic image from which each of the plurality of feature structures is detected is a focal plane; and derive the misregistration amount in the corresponding tomographic plane determined as the focal plane (Morita - [0020] “In the tomographic image generating apparatus according to the aspect of the present disclosure, the feature point detecting unit may detect a plurality of the feature points from the plurality of tomographic images, the tomographic image generating apparatus may further comprise a focal plane discrimination unit that discriminates whether the corresponding tomographic plane corresponding to the tomographic image in which each of the plurality of feature points is detected is a focal plane, and the positional shift amount derivation unit may derive the positional shift amount on the corresponding tomographic plane which is discriminated to be the focal plane.” wherein feature structures are feature points and a misregistration amount is a positional shift amount) (Sendai - [0063] “The determination of breast type is performed in the following manner. First, the breast type determining part 31a extracts a region, where the breast is shown, from the X-ray image represented by the X-ray image data. For example, a pixel having a value of X-ray image data that is equal to or larger than a predetermined value and has a difference between values of X-ray image data in surrounding pixels and itself equal to or larger than a predetermined value is determined to be a boundary of the breast region.” wherein a feature structure is a breast region).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 6, Morita in view of Sendai teaches the image processing apparatus according to claim 5,
wherein the at least one processor is configured to detect, as the feature structure, a point at which a specific threshold value condition is satisfied in the feature-structure tomographic image (Morita - [0134] “Returning to the processing of step ST13, the feature point detecting unit 33 detects the feature point from the plurality of new tomographic images, in step ST14, the projection unit 34 acquires a plurality of new tomographic plane projection images, and the positional shift amount derivation unit 35 derives a new positional shift amount between the plurality of new tomographic plane projection images in step ST15, and determines whether the positional shift amount is equal to or smaller than the predetermined threshold Th1 in step ST16.”) (Sendai - [0063] “The determination of breast type is performed in the following manner. First, the breast type determining part 31a extracts a region, where the breast is shown, from the X-ray image represented by the X-ray image data. For example, a pixel having a value of X-ray image data that is equal to or larger than a predetermined value and has a difference between values of X-ray image data in surrounding pixels and itself equal to or larger than a predetermined value is determined to be a boundary of the breast region.” wherein a feature structure is a breast region).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 7, Morita in view of Sendai teaches the image processing apparatus according to claim 6,
wherein the at least one processor is configured to:
update the feature-structure tomographic image by reconstructing the feature-structure projection images while correcting the misregistration; detect an updated feature structure from the updated feature-structure tomographic image; update the misregistration amount using the updated feature structure; and repeat the update of the feature-structure tomographic image, the update of the feature structure, and the update of the misregistration amount (Morita - [0022] “In the tomographic image generating apparatus according to the aspect of the present disclosure, the reconstruction unit may reconstruct all or a part of the plurality of projection images while correcting the positional shift amount to generate a plurality of the corrected tomographic images on the plurality of tomographic planes of the subject as a plurality of new tomographic images, the feature point detecting unit may detect the feature point from the plurality of new tomographic images, the positional shift amount derivation unit may derive a new positional shift amount between the plurality of new projection images, and the reconstruction unit may reconstruct the plurality of projection images while correcting the new positional shift amount to generate a new corrected tomographic image on at least one tomographic plane of the subject.” wherein a misregistration amount is a positional shift amount) (Morita - [0023] “In the tomographic image generating apparatus according to the aspect of the present disclosure, the reconstruction unit, the feature point detecting unit, and the positional shift amount derivation unit may repeat generating of the new tomographic image, detecting of the feature point from the new tomographic image, and deriving of the new positional shift amount until the new positional shift amount converges.” wherein a misregistration amount is a positional shift amount) (Sendai - [0063] “The determination of breast type is performed in the following manner. First, the breast type determining part 31a extracts a region, where the breast is shown, from the X-ray image represented by the X-ray image data. For example, a pixel having a value of X-ray image data that is equal to or larger than a predetermined value and has a difference between values of X-ray image data in surrounding pixels and itself equal to or larger than a predetermined value is determined to be a boundary of the breast region.” wherein a feature structure is a breast region).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 8, Morita in view of Sendai teaches the image processing apparatus according to claim 6,
wherein the at least one processor is configured to:
update the feature-structure tomographic image by reconstructing the feature-structure projection images while correcting the misregistration; detect an updated feature structure from the updated feature-structure tomographic image based on an updated threshold value condition; update the misregistration amount by using the updated feature structure; and repeat the update of the feature-structure tomographic image, the update of the feature structure based on the updated threshold value condition, and the update of the misregistration amount (Morita - [0022] “In the tomographic image generating apparatus according to the aspect of the present disclosure, the reconstruction unit may reconstruct all or a part of the plurality of projection images while correcting the positional shift amount to generate a plurality of the corrected tomographic images on the plurality of tomographic planes of the subject as a plurality of new tomographic images, the feature point detecting unit may detect the feature point from the plurality of new tomographic images, the positional shift amount derivation unit may derive a new positional shift amount between the plurality of new projection images, and the reconstruction unit may reconstruct the plurality of projection images while correcting the new positional shift amount to generate a new corrected tomographic image on at least one tomographic plane of the subject.” wherein a misregistration amount is a positional shift amount) (Morita - [0023] “In the tomographic image generating apparatus according to the aspect of the present disclosure, the reconstruction unit, the feature point detecting unit, and the positional shift amount derivation unit may repeat generating of the new tomographic image, detecting of the feature point from the new tomographic image, and deriving of the new positional shift amount until the new positional shift amount converges.” wherein a misregistration amount is a positional shift amount) (Sendai - [0063] “The determination of breast type is performed in the following manner. First, the breast type determining part 31a extracts a region, where the breast is shown, from the X-ray image represented by the X-ray image data. For example, a pixel having a value of X-ray image data that is equal to or larger than a predetermined value and has a difference between values of X-ray image data in surrounding pixels and itself equal to or larger than a predetermined value is determined to be a boundary of the breast region.” wherein a feature structure is a breast region).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 9, Morita in view of Sendai teaches the image processing apparatus according to claim 4,
wherein the at least one processor is configured to:
derive a tomographic-plane projection image corresponding to each of the plurality of projection images by projecting the plurality of projection images onto the corresponding tomographic plane based on a positional relationship between the radiation source position and the detection unit when performing imaging for each of the plurality of projection images; and derive, in the corresponding tomographic plane, as the misregistration amount between the plurality of projection images, a misregistration amount between a plurality of the tomographic-plane projection images based on the body movement of the subject, by using, as a reference, the feature structure (Morita - [0012] “The tomographic image generating apparatus according the aspect of the present disclosure may further comprise a projection unit that projects the plurality of projection images on the corresponding tomographic plane based on a positional relationship between the radiation source position and the detection unit in a case of imaging the plurality of projection images to acquire a tomographic plane projection image corresponding to each of the plurality of projection images, in which the positional shift amount derivation unit derives, as the positional shift amount between the plurality of projection images, a positional shift amount between a plurality of the tomographic plane projection images based on the body movement of the subject with the feature point as a reference on the corresponding tomographic plane.” wherein a misregistration amount is a positional shift amount) (Sendai - [0063] “The determination of breast type is performed in the following manner. First, the breast type determining part 31a extracts a region, where the breast is shown, from the X-ray image represented by the X-ray image data. For example, a pixel having a value of X-ray image data that is equal to or larger than a predetermined value and has a difference between values of X-ray image data in surrounding pixels and itself equal to or larger than a predetermined value is determined to be a boundary of the breast region.” wherein a feature structure is a breast region).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 10, Morita in view of Sendai teaches the image processing apparatus according to claim 9,
wherein the at least one processor is configured to: set a local region corresponding to the feature structure in the plurality of tomographic-plane projection images; and derive the misregistration amount based on the local region (Morita - [0013] “In the tomographic image generating apparatus according to the aspect of the present disclosure, the positional shift amount derivation unit may set a local region corresponding to the feature point in the plurality of tomographic plane projection images, and derive the positional shift amount based on the local region.” wherein a misregistration amount is a positional shift amount).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 11, Morita in view of Sendai teaches the image processing apparatus according to claim 9,
wherein the at least one processor is configured to: set a plurality of first local regions including the feature structure in the plurality of tomographic-plane projection images; set a second local region including the feature structure in a tomographic image from which the feature structure is detected; derive misregistration amounts of the plurality of first local regions with respect to the second local region, as temporary misregistration amounts; and derive the misregistration amount based on a plurality of the temporary misregistration amounts (Morita - [0014] “In the tomographic image generating apparatus according to the aspect of the present disclosure, the positional shift amount derivation unit may set a plurality of first local regions including the feature point in the plurality of tomographic plane projection images, set a second local region including the feature point in the tomographic image in which the feature point is detected, derive a positional shift amount of each of the plurality of first local regions with respect to the second local region as a temporary positional shift amount, and derive the positional shift amount based on a plurality of the temporary positional shift amounts.” wherein misregistration amounts are positional shift amounts) (Sendai - [0063] “The determination of breast type is performed in the following manner. First, the breast type determining part 31a extracts a region, where the breast is shown, from the X-ray image represented by the X-ray image data. For example, a pixel having a value of X-ray image data that is equal to or larger than a predetermined value and has a difference between values of X-ray image data in surrounding pixels and itself equal to or larger than a predetermined value is determined to be a boundary of the breast region.” wherein a feature structure is a breast region).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 12, Morita in view of Sendai teaches the image processing apparatus according to claim 11,
wherein the at least one processor is configured to derive the temporary misregistration amounts based on a region around the feature structure in the second local region (Morita - [0015] “In this case, the positional shift amount derivation unit may derive the temporary positional shift amount based on a peripheral region of the feature point in the second local region.” wherein misregistration amounts are positional shift amounts) (Sendai - [0063] “The determination of breast type is performed in the following manner. First, the breast type determining part 31a extracts a region, where the breast is shown, from the X-ray image represented by the X-ray image data. For example, a pixel having a value of X-ray image data that is equal to or larger than a predetermined value and has a difference between values of X-ray image data in surrounding pixels and itself equal to or larger than a predetermined value is determined to be a boundary of the breast region.” wherein a feature structure is a breast region).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 13, Morita in view of Sendai teaches the image processing apparatus according to claim 11,
wherein the at least one processor is configured to:
derive a plurality of the tomographic images as target tomographic images by reconstructing the plurality of projection images excluding a target projection image corresponding to a target tomographic-plane projection image that is a target for deriving the misregistration amount; and derive the misregistration amount for the target tomographic-plane projection image by using the target tomographic image (Morita - [0019] “In the tomographic image generating apparatus according to the aspect of the present disclosure, the reconstruction unit may reconstruct the plurality of projection images excluding a target projection image which corresponds to a target tomographic plane projection image of which the positional shift amount is to be derived, and generates the plurality of tomographic images as target tomographic images, and the positional shift amount derivation unit may derive the positional shift amount of the target tomographic plane projection image by using the target tomographic images.”).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 14, Morita in view of Sendai teaches the image processing apparatus according to claim 4,
wherein the at least one processor is configured to: perform image quality evaluation of a region of interest including the feature structure in the corrected tomographic image; and determine whether the derived misregistration amount is appropriate or inappropriate based on a result of the image quality evaluation (Morita - [0025] “The tomographic image generating apparatus according to the aspect of the present disclosure may further comprise a positional shift amount determination unit that performs image quality evaluation for a region of interest including the feature point in the corrected tomographic image, and determines whether the derived positional shift amount is appropriate or inappropriate based on a result of the image quality evaluation.” wherein a derived misregistration amount is a derived positional shift amount).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 15, Morita in view of Sendai teaches the image processing apparatus according to claim 14,
wherein the at least one processor is configured to:
derive a plurality of tomographic images by reconstructing the plurality of projection images (Morita - [0030] “reconstructing all or a part of the plurality of projection images to generate a tomographic image on each of a plurality of tomographic planes of the subject,”); and
perform image quality evaluation of a region of interest including the feature structure in the tomographic image; compare the result of the image quality evaluation for the corrected tomographic image with a result of the image quality evaluation for the tomographic image; and determine a tomographic image of which the result of the image quality evaluation is better as a final tomographic image (Morita - [0026] “In the tomographic image generating apparatus according to the aspect of the present disclosure, the positional shift amount determination unit may perform the image quality evaluation for the region of interest including the feature point in the tomographic image, compare the result of the image quality evaluation for the corrected tomographic image with a result of the image quality evaluation for the tomographic image, and decide the tomographic image with a better result of the image quality evaluation as a final tomographic image.”) (Sendai - [0063] “The determination of breast type is performed in the following manner. First, the breast type determining part 31a extracts a region, where the breast is shown, from the X-ray image represented by the X-ray image data. For example, a pixel having a value of X-ray image data that is equal to or larger than a predetermined value and has a difference between values of X-ray image data in surrounding pixels and itself equal to or larger than a predetermined value is determined to be a boundary of the breast region.” wherein a feature structure is a breast region).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 16, Morita in view of Sendai teaches the image processing apparatus according to claim 4,
wherein the at least one processor is configured to:
derive an evaluation function for performing image quality evaluation of a region of interest including the feature structure in the corrected tomographic image; and derive the misregistration amount for optimizing the evaluation function (Morita - [0027] “The tomographic image generating apparatus according to the aspect of the present disclosure may further comprise an evaluation function derivation unit that derives an evaluation function for performing image quality evaluation for a region of interest including the feature point in the corrected tomographic image, in which the positional shift amount derivation unit derives the positional shift amount for optimizing the evaluation function.” wherein a feature structure is a feature point) (Sendai - [0063] “The determination of breast type is performed in the following manner. First, the breast type determining part 31a extracts a region, where the breast is shown, from the X-ray image represented by the X-ray image data. For example, a pixel having a value of X-ray image data that is equal to or larger than a predetermined value and has a difference between values of X-ray image data in surrounding pixels and itself equal to or larger than a predetermined value is determined to be a boundary of the breast region.” wherein a feature structure is a breast region).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 17, Morita in view of Sendai teaches the image processing apparatus according to claim 1,
wherein the subject is a breast (Morita - [0028] “In the tomographic image generating apparatus according to the aspect of the present disclosure, the subject may be a breast.”).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 18, Morita in view of Sendai teaches the image processing apparatus according to claim 17,
wherein the at least one processor is configured to change a search range in derivation of a misregistration amount according to at least one of a density of a mammary gland, a size of the breast, an imaging time of the tomosynthesis imaging, a compression pressure of the breast in the tomosynthesis imaging, or an imaging direction of the breast (Morita - [0029] “In the tomographic image generating apparatus according the aspect of the present disclosure, the positional shift amount derivation unit may change a search range in a case of deriving the positional shift amount depending on at least one of a density of a mammary gland, a size of the breast, an imaging time of the tomosynthesis imaging, a compression pressure of the breast in a case of the tomosynthesis imaging, or an imaging direction of the breast.”).
The motivation for combining Morita and Sendai is the same motivation as used for claim 1.
Regarding claim 19, the claim recites similar limitations to claim 1 but in the form of a method. Therefore, claim 19 recites similar limitations to claim 1 and is rejected for similar rationale and reasoning (see the analysis for claim 1 above).
Regarding claim 20, the claim recites similar limitations to claim 1 but in the form of a non-transitory storage medium storing a program causing a computer to execute the apparatus of claim 1 (Morita - [0075] “The tomographic image generating program is distributed in a state of being recorded on a recording medium such as a digital versatile disc (DVD) or a compact disc read only memory (CD-ROM), and is installed in the computer from the recording medium. Alternatively, the tomographic image generating program is stored in a storage device of a server computer connected to the network, or in a network storage so as to be accessible from the outside, and is downloaded and installed in the computer as necessary.”). Therefore, claim 19 recites similar limitations to claim 1 and is rejected for similar rationale and reasoning (see the analysis for claim 1 above).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AMANDA PEARSON whose telephone number is (703)-756-5786. The examiner can normally be reached Monday - Friday 9:00 - 5:00.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Emily Terrell can be reached on (571)- 270-3717. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/AMANDA H PEARSON/Examiner, Art Unit 2666
/MING Y HON/Primary Examiner, Art Unit 2666
Prosecution Insights