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 .
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1-4, 6-7, 10-11, 13, 15 and 17-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ranchod (PGPUB 20130271728, of record) in view of Russakoff et al. (PGPUB 20210369195).
Regarding claim 1, Ranchod discloses a method comprising:
illuminating a region of a choroid of an eye of a patient with off-axis illumination from a first imaging channel, the first imaging channel being off-axis with respect to an axis of a focus of the eye (See Fig. 4, [0010] where 200 represents a plurality of non-coaxial paths that illuminate the fundus, which comprises the choroid);
capturing an image of the choroid using an image sensor (Fig. 4 where there are 3 distinct sensors, 220) in the first imaging channel ([0003] and [0018]), the off-axis illumination from the first imaging channel being off-set within the first imaging channel from the image sensor (Fig. 4).
Ranchod does not disclose providing the captured image to a machine learning system for processing by a machine learning model trained to process image data using a set of choroidal images and, for each choroidal image of the set of choroidal images, at least one of:
a set of indices relating to a choroid of the choroidal image, or a set of factors relating to an individual from which the choroidal image was captured.
However, Russakoff teaches an eye imaging method ([0008] 2D images) that includes imaging the choroid ([0059]) and providing the captured image to a machine learning system for processing by a machine learning model trained to process image data using a set of choroidal images and, for each choroidal image of the set of choroidal images ([0059]), at least one of:
a set of indices relating to a choroid of the choroidal image, or a set of factors relating to an individual from which the choroidal image was captured ([0059]).
It would have been obvious to one having ordinary skill in the art as of the effective filing date of the invention to combine Ranchod and Wao such that the image data was provided to a machine learning algorithm motivated by improving diagnostic accuracy (Abst).
Regarding claim 2, modified Ranchod discloses wherein illuminating the region of the choroid of the patient further comprises illuminating the region of the choroid with a second off-axis illumination from a second imaging channel that is off-axis from both the first imaging channel and the off-axis illumination (See Fig. 4, [0010] where 200 represents a plurality of non-coaxial paths that illuminate the fundus).
Regarding claim 3, modified Ranchod discloses wherein the first imaging channel and the off-axis illumination capture a first image of the choroid of the eye and the second imaging channel and the second off-axis illumination capture a second image of the choroid of the eye (Fig. 8), the first image and the second image having an overlapping region, the method further comprising combining the first image and the second image into a single image, the single image having a wider field of view than either of the first image or the second image ([0003] and Fig. 8 shows 11n, c and t overlapping such that they result in a large field of view than a single image).
Regarding claim 4, as best understood, modified Ranchod discloses further comprising processing the captured image, comprising:
filtering out a first color of light present in the captured image ([0018]-[0019]); and
emphasizing a second color of light present in the captured image ([0018]-[0019]).
Regarding claim 6, modified Ranchod discloses wherein the off-axis illumination is a wide-spectrum light source ([0018]).
Regarding claim 7, modified Ranchod discloses wherein the wide-spectrum light source is a bright white light-emitting diode (LED) ([0010] and [0018]).
Regarding claim 10, modified Ranchod discloses wherein capturing the image of the choroid further comprises capturing a series of images of the choroid ([0020]).
Regarding claim 11, modified Ranchod discloses wherein the series of images of the choroid has a common focus depth and a common wavelength of illumination ([0011]).
Regarding claim 13, modified Ranchod discloses further comprising combining the series of images of the choroid to produce a video of the choroid ([0020]).
Regarding claim 15, modified Ranchod discloses further comprising identifying one or more indices based on an output of the machine learning system (at least [0010] of Russakoff).
Regarding claim 17, modified Ranchod discloses wherein the one or more indices are identified based on a region of the image of the choroid that is smaller than the entire image of the choroid using the machine learning system ([0101] of Russakoff).
Regarding claim 18, modified Ranchod discloses further comprising training the machine learning system to identify, based on image data, one or more specific diseases based on the one or more identified indices (see at least [0008] of Russakoff).
Regarding claim 19, Ranchod discloses a method of conducting an eye exam comprising:
illuminating a region of a choroid of an eye of a patient with off-axis illumination from a first imaging channel (See Fig. 4, [0010] where 200 represents a plurality of non-coaxial paths that illuminate the fundus, which comprises the choroid);
capturing a first image of the choroid before an intervention using an image sensor in the first imaging channel (Fig. 4 where there are 3 distinct sensors, 220), the off-axis illumination from the first imaging channel being off- set within the first imaging channel from the image sensor (Fig. 4);
capturing a second image of the choroid after the intervention using the image sensor in the first imaging channel (See Fig. 4, [0010] and 220, and where 200 represents a plurality of non-coaxial paths that illuminate the fundus and [0065] where images are taken before and after treatment for particular diseases); and
comparing one or more features within at least two images so that one may identify the effects of an intervention based on the comparing the one or more first indices to the one or more second indices ([0065]).
Ranchod does not wherein the computer processing comprises processing by a machine learning model trained to process image data using a set of choroidal images and, for each respective choroidal image of the set of choroidal images, at least one of:a set of indices relating to a choroid of the respective choroidal image, or a set of factors relating to an individual from which the respective choroidal image was captured;
disclose wherein identifying one or more first indices based on computer processing of the first image of the choroid;
identifying one or more second indices based on computer processing of the second image of the choroid;
comparing the one or more first indices to the one or more second indices; and
identifying effects of the intervention based on the comparing the one or more first indices to the one or more second indices.
However, Russakoff teaches an eye imaging method ([0008] 2D images) that includes imaging the choroid ([0059]) and providing the captured image to a machine learning system for processing by a machine learning model trained to process image data using a set of choroidal images and, for each choroidal image of the set of choroidal images ([0059]), at least one of:
a set of indices relating to a choroid of the choroidal image, or a set of factors relating to an individual from which the choroidal image was captured ([0059]);
disclose wherein identifying one or more first indices based on computer processing of the first image of the choroid ([0101]);
identifying one or more second indices based on computer processing of the second image of the choroid ([0101]);
comparing the one or more first indices to the one or more second indices ([0015]); and
identifying effects of the intervention based on the comparing the one or more first indices to the one or more second indices ([0015] monitoring disease status over time).
It would have been obvious to one having ordinary skill in the art as of the effective filing date of the invention to combine Ranchod and Wao such that the image data was provided to a machine learning algorithm motivated by improving diagnostic accuracy (Abst).
Regarding claim 20, Ranchod discloses a method of performing choroidal imaging using a handheld imaging device, the method comprising:
illuminating a region of a choroid of an eye of a patient with off-axis illumination from a first imaging channel (See Fig. 4, [0010] where 200 represents a plurality of non-coaxial paths that illuminate the fundus, which comprises the choroid);
capturing a first image of the choroid using an image sensor in the first imaging channel (220 and Fig. 4), the off-axis illumination from the first imaging channel being off-set within the first imaging channel from the image sensor (Fig. 4);
capturing a second image of the choroid using the image sensor in the first imaging channel (220 and Fig. 4).
Ranchod does not disclose wherein the computer processing comprises processing by a machine learning model trained to process image data using a set of choroidal images and, for each respective choroidal image of the set of choroidal images, at least one of: a set of indices relating to a choroid of the respective choroidal image, or a set of factors relating to an individual from which the respective choroidal image was captured;
identifying one or more first indices based on computer processing of the first image of the choroid; and
identifying one or more second indices based on computer processing of the second image of the choroid.
However, Russakoff teaches an eye imaging method ([0008] 2D images) that includes imaging the choroid ([0059]) and providing the captured image to a machine learning system for processing by a machine learning model trained to process image data using a set of choroidal images and, for each choroidal image of the set of choroidal images ([0059]), at least one of:
a set of indices relating to a choroid of the choroidal image, or a set of factors relating to an individual from which the choroidal image was captured ([0059]);
disclose wherein identifying one or more first indices based on computer processing of the first image of the choroid ([0101]);
identifying one or more second indices based on computer processing of the second image of the choroid ([0101]);
comparing the one or more first indices to the one or more second indices ([0015]); and
identifying effects of the intervention based on the comparing the one or more first indices to the one or more second indices ([0015] monitoring disease status over time).
It would have been obvious to one having ordinary skill in the art as of the effective filing date of the invention to combine Ranchod and Wao such that the image data was provided to a machine learning algorithm motivated by improving diagnostic accuracy (Abst).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ranchod in view of Russakoff and further in view of Yogesan et al. (PGPUB 20130083184).
Regarding claim 5, modified Ranchod teaches modification particular light wavelengths to enhance imaging ([0018]-[0019]), but does not specifically disclose wherein the second wavelength of light is associated with a red color.
However, Yogesan teaches a choroid imaging device wherein red colored light is used to enhance choroid features within the eye ([0033]).
It would have been obvious to one having ordinary skill in the art as of the effective filing date of the invention to combine modified Ranchod and Yogesan such that red light was used to enhance choroid features motivated by improving imaging quality ([0033]).
Claim(s) 8-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ranchod in view of Russakoff and further in view of Wiles et al. (PGPUB 20140359798).
Regarding claim 8, modified Ranchod does not disclose further comprising sharpening the captured image by applying an unsharp mask to the captured image.
However, Wiles teaches a method of imaging vessels within an eye ([0231]) comprising sharpening the captured image by applying an unsharp mask to the captured image ([0231]).
It would have been obvious to one having ordinary skill in the art as of the effective filing date of the invention to combine modified Ranchod and Wiles such that images were sharpened with an unsharp mask motivated by improving image quality.
Regarding claim 9, modified Ranchod discloses further comprising determining a sharpening radius for detecting edges, the sharpening radius corresponding to a target layer of choroidal vessels of the choroid of the eye with a target size, the sharpening radius used in sharpening the captured image ([0231]-[0232] of Wiles).
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ranchod in view of Russakoff and further in view of Wang (PGPUB 20160249804 hereinafter Wang’9804).
Regarding claim 12, modified Ranchod teaches a optical system having a high depth of field ([0047]), but does not disclose wherein the series of images of the choroid has more than one focus depth.
However, Wang’9804 teaches a fundus imaging method ([0015]) wherein the series of images of the choroid has more than one focus depth ([0004]).
It would have been obvious to one having ordinary skill in the art as of the effective filing date of the invention to combine modified Ranchod and Wang’9804 such that the plurality of images were taken at more than one focus depth motivated by improving the diagnosis for particular diseases ([0001]).
Claim(s) 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ranchod in view of Russakoff and further in view of Samec et al. (PGPUB 20160270656).
Regarding claim 14, modified Ranchod does not disclose further comprising identifying a heartbeat by analyzing flow through choroidal vessels in the video of the choroid.
However, Samec teaches a method of imaging an eye ([1743]) wherein a an ocular pulse is determined by imaging the eye ([1742]-[1743]).
It would have been obvious to one having ordinary skill in the art as of the effective filing date of the invention to combine modified Ranchod and Samec such that the optical pulse was measured motivated by improving the diagnosis for particular diseases ([1744]).
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ranchod in view of Russakoff and further in view of El-Baz et al. (PGPUB 20200178794).
Regarding claim 16, modified Ranchod does not disclose wherein the one or more indices include at least one of average choroidal vascular caliber, average choroidal vascular tortuosity, ratio of choroidal vascular caliber to retinal vascular caliber, ratio of choroidal vascular tortuosity to retinal vascular tortuosity, categorization based on choroidal branching patterns, or choroidal vascular density.
However, El-Baz teaches a fundus imaging method ([0004]) wherein a machine learning algorithm is used to extract retinal features to include local density of retinal blood vessels and caliber of retinal vessels ([0091]).
It would have been obvious to one having ordinary skill in the art as of the effective filing date of the invention to combine modified Ranchod and El-Baz such that a local density or caliber of the choroid vessels was extracted by the machine learning algorithm motivated by improving the diagnosis for particular diseases ([0002]).
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because of a new grounds for rejection.
Applicant’s remarks are directed towards Wang, which is no longer relied upon in this rejection.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Mao et al. (PGPUB 20190259163) – imaging of choroid and analysis thereof using machine learning
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.
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/TRAVIS S FISSEL/Primary Examiner, Art Unit 2872