DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments, see pages 6-9, filed9/10/25, with respect to the rejection(s) of claim(s) 1-20 under 35 U.S.C. 103 and 102(a)(1) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of U.S. patent application publication 2022/0361744 by Devani.
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, 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.
1) Claim(s) 1, 2, 9, 11 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. patent application publication 2022/0361744 by Devani, and further in view of U.S. patent application publication 2016/0148047 by Jung, and further in view of U.S. patent application publication 2020/0093362 by Jackson et al.
2) Regarding claim 1, Devani teaches an eye imager, comprising: a camera (paragraph 69; camera can emit IR light and capture IR images); at least one processing device in communication with the camera; and at least one computer readable data storage device storing instructions which, when executed by the at least one processing device (paragraph 66; a processor and a memory), cause the eye imager to: determine whether a cataract is detected in the infrared image (paragraph 115; cataract can be determined); and perform an action based on detection of the cataract (paragraph 90; health status is determined and can be displayed as noted in paragraph 92).
Devani does not specifically teach a camera having at least one infrared LED (emission of IR is disclosed but not specifically from an LED); capture a sequence of infrared images of an eye using the camera; select an infrared image from the sequence of infrared images.
Jung teaches capture a sequence of infrared images of an eye using the camera; select an infrared image from the sequence of infrared images (paragraph 91; figure 11; series of images can be captured and one selected for use in diagnosis).
Devani and Jung are combinable because both are from the eye imaging field of endeavor.
It would have been obvious to a person of ordinary skill in the art at the time the invention was effectively filed to combine Devani with Jung to add selection of an image from a series. The motivation for doing so would have been to select an image with the “highest focus quality” (paragraph 91).
Jackson teaches one infrared LED (paragraphs 51 and 205; infrared emission can be from an LED).
Devani and Jackson are combinable because both are from the eye imaging field of endeavor.
It would have been obvious to a person of ordinary skill in the art at the time the invention was effectively filed to combine Devani with Jackson to add an IR LED. The motivation for doing so would have been to generate an image of a subject’s eye (paragraph 94).
Therefore it would have been obvious to combine Devani with Jung and Jackson to obtain the invention of claim 1.
3) Regarding claim 2, Jung (as combined with Walsh in the rejection of claim 1 above) teaches the eye imager of claim 1, wherein the infrared image is selected by identifying an image with a highest standard deviation in Laplacian distribution of pixels (paragraphs 87 and 91; best focus from Laplacian distribution is chosen).
4) Regarding claim 9, Devani teaches the eye imager of claim 1, wherein the instructions, when executed by the at least one processing device, further cause the eye imager to: generate a curve of pixel intensities inside a bright region of a pupil (paragraphs 111; figure 8; histogram of pixel intensities is created).
5) Claims 11 and 12 are taught in the same manner as described in the rejection of claims 1 and 2 above, respectively.
6) Claim(s) 3, 10, 13 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. patent application publication 2022/0361744 by Devani, and further in view of U.S. patent application publication 2016/0148047 by Jung, and further in view of U.S. patent application publication 2020/0093362 by Jackson et al., as applied to the rejection of claim 1 above, and further in view of U.S. patent application publication 2021/0386285 by Walsh et al.
7) Regarding claim 3, Devani does not specifically teach the eye imager of claim 1, wherein the action includes generate a recommendation to follow up with an eye care professional.
Walsh teaches the eye imager of claim 1, wherein the action includes generate a recommendation to follow up with an eye care professional (figure 11B; paragraph 212; diagnosis is recorded and recommendations given to patient).
Devani and Walsh are combinable because both are from the eye imaging field of endeavor.
It would have been obvious to a person of ordinary skill in the art at the time the invention was effectively filed to combine Devani with Walsh to add patient recommendations. The motivation for doing so would have been to inform a patient. Therefore it would have been obvious to combine Devani with Walsh to obtain the invention of claim 3.
8) Regarding claim 10, Walsh (as combined with Devani in the rejection of claim 3 above) teaches the eye imager of claim 9, wherein the instructions, when executed by the at least one processing device, further cause the eye imager to: store a cataract profile for at least one type of cataract; and classify the cataract as belonging to the at least one type of cataract by comparing the curve of pixel intensities to the cataract profile (paragraph 237; profile [i.e. nomogram] of cataract is compared with imaging data).
9) Claims 13 and 16 are taught in the same manner as described in the rejection of claims 3 and 10 above, respectively.
10) Claim(s) 4, 7, 8, 14 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. patent application publication 2022/0361744 by Devani, and further in view of U.S. patent application publication 2016/0148047 by Jung, and further in view of U.S. patent application publication 2020/0093362 by Jackson et al., as applied to the rejection of claim 1 above, and further in view of U.S. patent application publication 2019/0365218 by Okamoto et al.
11) Regarding claim 4, Devani does not specifically teach the eye imager of claim 1, wherein the cataract is detected by identifying an artifact in a bright region of a pupil in the infrared image
Okamoto teaches the eye imager of claim 1, wherein the cataract is detected by identifying an artifact in a bright region of a pupil in the infrared image (paragraphs 56; artifact can be identified in the pupil).
Devani and Okamoto are combinable because both are from the eye imaging field of endeavor.
It would have been obvious to a person of ordinary skill in the art at the time the invention was effectively filed to combine Devani with Okamoto to add scoring based on region ratio. The motivation for doing so would have been to analyze the subject eye (paragraph 4). Therefore it would have been obvious to combine Devani with Okamoto to obtain the invention of claim 4.
12) Regarding claim 7, Okamoto (as combined with Devani in the rejection of claim 4 above) teaches the eye imager of claim 4, wherein the instructions, when executed by the at least one processing device, further cause the eye imager to: segment the artifact from the bright region of the pupil (paragraph 20; tissue boundaries are detected); determine a surface area of the artifact; and calculate a score based on a ratio of the surface area of the artifact to a surface area of the bright region of the pupil, and wherein the cataract is detected when the score exceeds a predetermined threshold (paragraphs 50, 54 and 56; opacity defect is graded based upon opacity ratio of the region).
13) Regarding claim 8, Devani teaches the eye imager of claim 7, wherein the instructions, when executed by the at least one processing device, further cause the eye imager to: store the score in an electronic medical record of a patient for monitoring progression of the cataract over time (paragraphs 62 and 90; progression of disease can be stored and monitored over time).
14) Claims 14 and 15 are taught in the same manner as described in the rejections of claims 4 and 7 above, respectively.
15) Claim(s) 5 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. patent application publication 2022/0361744 by Devani, and further in view of U.S. patent application publication 2016/0148047 by Jung, and further in view of U.S. patent application publication 2020/0093362 by Jackson et al., and further in view of U.S. patent application publication 2019/0365218 by Okamoto et al. as applied to the rejection of claim 4 above, and further in view of U.S. patent application publication 2012/0155726 by Li et al.
16) Regarding claim 5, Devani does not specifically teach the eye imager of claim 4, wherein the instructions, when executed by the at least one processing device, further cause the eye imager to: use a machine learning model to confirm the artifact is a type of cataract.
Li teaches the eye imager of claim 4, wherein the instructions, when executed by the at least one processing device, further cause the eye imager to: use a machine learning model to confirm the artifact is a type of cataract (paragraphs 51 and 52; trained SVM is used to detect cataracts).
Devani and Li are combinable because both are from the eye imaging field of endeavor.
It would have been obvious to a person of ordinary skill in the art at the time the invention was effectively filed to combine Devani with Li to add machine learning. The motivation for doing so would have been for “automatic diagnosis” (paragraph 4). Therefore it would have been obvious to combine Devani with Li to obtain the invention of claim 5.
17) Regarding claim 6, Li (as combined with Devani in the rejection of claim 5 above) teaches the eye imager of claim 4, wherein the instructions, when executed by the at least one processing device, further cause the eye imager to: use a machine learning model to classify the artifact as a type of cataract selected from the group consisting of an early-onset cataract, a nuclear cataract, a cortical cataract, and a posterior capsular cataract (paragraphs 3 and 52; nuclear, cortical and posterior capsular are disclosed, a low severity rating would indicate an early-onset cataract).
18) Claim(s) 17 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. patent application publication 2022/0361744 by Devani, and further in view of U.S. patent application publication 2019/0365218 by Okamoto et al., and further in view of U.S. patent application publication 2021/0386285 by Walsh et al.
19) Regarding claim 17, Devani teaches an eye imager, comprising: at least one processing device; and at least one computer readable data storage device storing instructions which, when executed by the at least one processing device (paragraph 66; a processor and a memory), cause the eye imager to: capture an infrared image of an eye (paragraph 69; camera can emit IR light and capture IR images); segment a region of a pupil in the infrared image from a region of an iris in the infrared image (paragraphs 110-112; pupil and iris are segmented); extract features from the region of the pupil; generate a curve based on the features (paragraphs 111; figure 8; histogram of pixel intensities, including pupil, is created, each point within the pupil being a feature).
Devani does not specifically teach a bright region of a pupil, a dark region of an iris; and detect a cataract based on a comparison of the curve to a cataract profile.
Okamoto teaches a bright region of a pupil, a dark region of an iris (figure 8B; pupil is bright while iris is dark as shown and can be obtained from infrared imaging data as disclosed in paragraph 63).
Devani and Okamoto are combinable because both are from the eye imaging field of endeavor.
It would have been obvious to a person of ordinary skill in the art at the time the invention was effectively filed to combine Devani with Okamoto to add detecting a pupil as bright and the iris as dark. The motivation for doing so would have been to analyze the subject eye (paragraph 4).
Walsh teaches detecting a cataract based on a comparison of the curve to a cataract profile (paragraph 237; profile [i.e. nomogram] of cataract is compared with imaging data).
NOTE: cataract detection technique could be applied to infrared segmentation data of Devani, Okamoto also discloses that OCT data can be obtained through infrared light emission.
Devani and Walsh are combinable because both are from the eye imaging field of endeavor.
It would have been obvious to a person of ordinary skill in the art at the time the invention was effectively filed to combine Devani with Walsh to add detecting a cataract based on a profile. The motivation for doing so would have been to detect disease (paragraph 237).
Therefore it would have been obvious to combine Devani with Okamoto and Walsh to obtain the invention of claim 17.
20) Regarding claim 18, Devani teaches the eye imager of claim 17, wherein the features extracted from the bright region of the pupil are pixel intensity values (paragraphs 111; figure 8; histogram of pixel intensities, including pupil, is created).
21) Claim(s) 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. patent application publication 2022/0361744 by Devani, and further in view of U.S. patent application publication 2019/0365218 by Okamoto et al., and further in view of U.S. patent application publication 2021/0386285 by Walsh et al. as applied to claim 17 above, and further in view of U.S. patent application publication 2012/0155726 by Li et al.
22) Claims 19 and 20 are taught in the same manner as described in the rejection of claims 6 and 5 above, respectively.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BENJAMIN O DULANEY whose telephone number is (571)272-2874. The examiner can normally be reached Mon-Fri 10-6.
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BENJAMIN O. DULANEY
Primary Examiner
Art Unit 2676
/BENJAMIN O DULANEY/Primary Examiner, Art Unit 2683
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