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 .
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 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.
DETAILED ACTION
Response to Arguments
Applicant argues that Dast is limited to generating a current 2D representation of a sub-volume in current OCT volume data from a current doctor’s visit, but hat the method is likely to fail of the images or low quality or there are changes in either 2D representation. Applicant asserts that the present invention is directed to a plurality of 2D representations generated from a single sub-volume and that the plurality of 2D representations result in an increased number of matched characteristic features.
The examiner appreciates applicant’s description of the invention and attempt to distinguish the art. However, while one interpretation of the claim language would support applicant’s argument, the examiner is obliged to give the claims their broadest reasonable interpretation. Here, the broadest reasonable interpretation of a mixture set includes any two possible registration parameters. The examiner welcomes applicant to amend the claims specifically
With respect to claim 6, Dast ¶148 discloses additional displays such as thickness maps, difference maps, and pathology maps. Each map is derived from the image pair and for a particular sub-volume. The examiner notes that sub-volume is a largely meaningless designation as any sub portion of the eye could be a sub-volume.
Similarly with respect to claim 7, a curvature map is a broad descriptive term that encompasses more than applicant argues. For example, the images of the eye disclosed by Dast could also be a curvature map as it shows the curves of the eye and is therefore a “map” that illustrates the eye’s curvature at various points.
The examiner suggests that applicant amend these broad descriptive terms with more precise definitions as to avoid the ambiguity that come with these descriptive terms.
Information Disclosure Statement
Applicant is reminded of the duty to disclose information material to patentability. “Each individual associated with the filing and prosecution of a patent application has a duty of candor and good faith in dealing with the Office, which includes a duty to disclose to the Office all information known to that individual to be material to patentability as defined in this section. The duty to disclose information exists with respect to each pending claim until the claim is cancelled or withdrawn from consideration, or the application becomes abandoned. Information material to the patentability of a claim that is cancelled or withdrawn from consideration need not be submitted if the information is not material to the patentability of any claim remaining under consideration in the application.” This applies to:
(1) Each inventor named in the application;
(2) Each attorney or agent who prepares or prosecutes the application; and
(3) Every other person who is substantively involved in the preparation or prosecution of the application and who is associated with the inventor, the applicant, an assignee, or anyone to whom there is an obligation to assign the application.
37 CFR 1.56 and MPEP 2001.01.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-13, 16 are rejected under 35 USC 102 as being anticipated by 2017/0258321 Dastmalchi, et al. (hereafter Dast), assigned to applicant
1. (Currently Amended) A method of registering first optical coherence tomography (OCT) volume data to second OCT volume data, comprising:
generating a plurality of image pairs, each image pair including a two-dimensional (2D) representation of a sub-volume in the first OCT volume data and a corresponding 2D representation of the corresponding sub-volume in the second OCT volume data; (Dast ¶106 obtains two images (generated image pairs) of the same view/eye at different times)
for each image pair, identifying a local set of matching characteristic features in its corresponding 2D representations; (Dast ¶107 matches characteristics)
defining a mixture set of registration transformation parameters based on a global set of characteristic features based on a mixture of the local sets of matching characteristic features extracted from all of the image pairs; and (Dast ¶107-108 matching characteristics of the eye, note Dast indicates underlying structures, which is a mixture of matching characteristics; ¶108 includes ways to transform the images)
electronically processing, storing, or displaying the registration of the first OCT volume data and the second OCT volume data based on the set of registration transformation parameters. (Dast ¶110 images are registered to each other)
2. The method of claim 1, wherein the corresponding 2D representations in each image pair are en face structural images, en face angiography images, thickness maps, or curvature maps. (Dast ¶84 en face images, thickness maps)
3. The method of claim 1, wherein different image pairs include a mixture of two or more of en face structural images, en face angiography images, thickness maps, and curvature maps. (Dast ¶84 en face images, thickness maps)
4. The method of claim 1, wherein the 2D representations of different image pairs are based on different physical measures of its corresponding sub-volume. (Dast ¶93-94 different volumes from different regions etc.)
5. The method claim 1, wherein the sub-volume of a first of the image pairs is different from the sub-volume of a second of the image pairs. (Dast ¶93-94 different volumes from different regions etc.)
6. The method of claim 1, wherein at least a fraction of said the plurality of the image pairs includes a first image pair directly extracted from its corresponding sub-volume and a plurality of derived image pairs based on the first image pair. (Dast ¶147-148 additional displays based on the image pairs)
7. The method of claim 6, wherein the first image pair are corresponding thickness maps, and the plurality of derived image pairs are a corresponding plurality curvature maps each based on a different curvature characteristic of the corresponding thickness maps. (Dast ¶152 thickness maps of the eye show the shape of the eye, curvature is based on the thickness map)
8. The method of claim 6, wherein the first image pair are corresponding en face images, and the one or more derived images pairs are based on one or more of the image texture, color, intensity, contrast, and negative image of the en face images. (Dast ¶84 en face images; ¶111 different color channels)
9. The method of claim 1, wherein the first OCT volume data and the second OCT volume data are OCT structural volumes or OCT angiography volumes. (Dast ¶76 structure volume)
10. The method of claim 1, wherein the first OCT volume data is of a first region of a sample, the second OCT volume data is of a second region of the sample, the second region at least partially overlapping the first region. (Dast ¶106 different images, looking for the same structure, in both images, thus partial overlap given the same structure)
11. A method of registering optical coherence tomography (OCT) data, comprising:
accessing first OCT volume data of a first region of a sample; (Dast ¶76 structure volume)
accessing second OCT volume data of a second region of the sample, the second region at least partially overlapping the first region; (Dast ¶106 different images, looking for the same structure, in both images, thus partial overlap given the same structure)
generating a first set of a characteristic maps based on corresponding characteristic measures of one or more sub-volumes of the first OCT volume data; (Dast ¶106 obtains two images (generated image pairs) of the same view/eye at different times)
generating a second set of a characteristic maps each map in the second set having a one- to-one correspondence with a map in the first set, and each map in the second set being based on its corresponding characteristic measure of corresponding one or more sub-volumes of the second OCT volume data; (Dast ¶107 matches characteristics)
registering to each other corresponding maps in the first set and the second set, as group, to identify registration parameters for the first OCT volume data and the second OCT volume data; and (Dast ¶110 images are registered to each other)
storing or displaying the registration of the first OCT volume data and the second OCT volume data. (Dast ¶110 images are registered to each other)
12. The method of claim 11, wherein the characteristic maps include one or more thickness map of the first OCT volume data and the second OCT volume data. (Dast ¶152 thickness maps, curvature is based on the thickness map)
13. The method of claim 11, wherein the characteristic maps include one or more curvature maps of the first OCT volume data and the second OCT volume data. (Dast ¶152 thickness maps, curvature is based on the thickness map)
16. The method of claim 1, wherein the corresponding 2D representations in one or more of the plurality of image pairs include curvature maps. (Dast ¶152 thickness maps of the eye show the shape of the eye, curvature is based on the thickness map)
Claim Rejections - 35 USC § 103
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 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 14 and 15 are rejected under 35 USC 103 as being unpatentable over Dast in view of Deep Learning in Medical Imaging: General Overview, June-Goo Lee, Sanghoon Jun, Young-Won Cho, Hyunna Lee, Guk Bae Kim, Joon Beom Seo, MD, Namkug Kim, Korean Journal of Radiology, 2017 (hereafter Lee)
14. A method for identifying a fovea in OCT volume data, comprising:
defining a thickness map based on the OCT volume data; (Dast ¶152 thickness maps of the eye show the shape of the eye, curvature is based on the thickness map)
defining a plurality of curvature maps from the thickness map; and (Dast ¶152 thickness maps of the eye show the shape of the eye, curvature is based on the thickness map)
Dast ¶54 also locates the fovea
Dast does not disclose using a machine learning model to locate the fovea based on the thickness map and the plurality of curvature maps.
However, Lee discloses using machine learning as part of registering and identifying parts of radiological images. See pages 576-578. Lee describes the use of machine learning as having superior performance than humans in computer vision tasks. Therefore, it would have been obvious to modify the system of Dast to utilize machine learning to identify parts for the purposes of automatically annotating radiographs as taught by Lee as well as the application of a known technique to a known device ready for improvement with predictable results.
15. A method for identifying an optic nerve head in OCT volume data, comprising:
defining a thickness map based on the OCT volume data; (Dast ¶152 thickness maps of the eye show the shape of the eye, curvature is based on the thickness map)
defining a plurality of curvature maps from the thickness map; and (Dast ¶152 thickness maps of the eye show the shape of the eye, curvature is based on the thickness map)
Dast ¶54 also locates the optic nerve
Dast does not disclose
using a machine learning model to locate the optic nerve head based on the thickness map and the plurality of curvature maps.
However, Lee discloses using machine learning as part of registering and identifying parts of radiological images. See pages 576-578. Lee describes the use of machine learning as having superior performance than humans in computer vision tasks. Therefore, it would have been obvious to modify the system of Dast to utilize machine learning to identify parts for the purposes of automatically annotating radiographs as taught by Lee as well as the application of a known technique to a known device ready for improvement with predictable results.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Ming Shui whose telephone number is (303)297-4247. The examiner can normally be reached on 7-5 Pacific Time, M-Th.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Greg Morse can be reached on 571-272-38383838. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Ming Shui/
Primary Examiner, Art Unit 2663