Image retention and stitching for minimal-flash eye disease diagnosis
Systems and methods are provided herein for minimizing retinal exposure to flash during image gathering for diagnosis. In an embodiment, a system captures a plurality of retinal images of different retinal regions. The system determines that a first portion of a first image does not meet a criterion while a second portion of the first image does meet the criterion, identifies a portion of the retina depicted in the first portion that does not meet the criterion, and determines whether the portion of the retina is depicted in a third portion of a second image and whether the third portion meets the criterion. Responsive to determining that the third portion meets the criterion, the system performs the diagnosis. Responsive to determining that the portion of the retina is not depicted in the second image, the system captures an additional image of the retinal region.
1. A method for minimizing exposure of a retina to flash during image gathering for diagnosis, the method comprising:
capturing a first retinal image of a first retinal region by flashing the first retinal region responsive to determining a capturing device is focused on the first retinal region;
capturing a second retinal image of a second retinal region by flashing the second retinal region, the first retinal image and the second retinal image together forming a plurality of retinal images;
determining whether to again flash the first retinal region by:
determining that a first portion of the retina depicted in the first retinal image does not meet a quality criterion;
responsive to determining that the first portion of the retina does not meet the quality criterion, determining whether first portion of the retina is depicted in a second portion of the second retinal image;
responsive to determining that the first portion of the retina is depicted in the second portion of the second retinal image, determining whether a depiction of the first portion of the retina in the second portion meets the quality criterion; and
responsive to determining that the depiction in the second portion meets the quality criterion, determining not to again flash the first retinal region; and
passing the plurality of retinal images to a fully autonomous machine learning model that outputs a likelihood of a disease condition based on the plurality of retinal images.
2. The method of claim 1 , further comprising, responsive to determining that the second portion does not meet the quality criterion, determining to again flash the first retinal region to recapture the first retinal image.
3. The method of claim 1 , wherein capturing the first retinal image includes capturing a multi-frame video while the first retinal region is illuminated from the flashing, the flashing caused by a single flash, each frame of the multi-frame video capturing an image at a different level of flash exposure.
4. The method of claim 1 , wherein determining that the first portion of the first retinal image does not meet the quality criterion comprises determining that the first portion of the first retinal image is either over-exposed or under-exposed.
5. The method of claim 1 , wherein the second retinal image is an image of the retina of a same eye that the first retinal image depicts.
6. The method of claim 1 , wherein performing a diagnosis using the plurality of retinal images comprises:
generating a composite image comprising the first portion of the first retinal image with the second portion of the second retinal image stitched into the first retinal image; and
performing the diagnosis using the composite image.
7. The method of claim 1 , wherein performing a diagnosis using the plurality of retinal images comprises:
analyzing the first retinal image while discounting the first portion depicted in the first retinal image to generate a first analysis;
analyzing the second portion of the second retinal image to generate a second analysis; and
performing the diagnosis using the first analysis and the second analysis.
8. A computer program product for minimizing exposure of a retina to flash during image gathering for diagnosis, the computer program product comprising a non-transitory computer-readable storage medium containing computer program code for:
capturing a first retinal image of a first retinal region by flashing the first retinal region responsive to determining a capturing device is focused on the first retinal region;
capturing a second retinal image of a second retinal region by flashing the second retinal region, the first retinal image and the second retinal image together forming a plurality of retinal images;
determining whether to again flash the first retinal region by:
determining that a first portion of the retina depicted in the first retinal image does not meet a quality criterion;
responsive to determining that the first portion of the retina does not meet the quality criterion, determining whether the first portion of the retina is depicted in a second portion of the second retinal image;
responsive to determining that the first portion of the retina is depicted in the second portion of the second retinal image, determining whether a depiction of the first portion of the retina in the second portion meets the quality criterion; and
responsive to determining that the depiction in the second portion meets the quality criterion, determining not to again flash the first retinal region; and
passing the plurality of retinal images to a fully autonomous machine learning model that outputs a likelihood of a disease condition based on the plurality of retinal images.
9. The computer program product of claim 8 , the computer program code further for, responsive to determining that the second portion does not meet the quality criterion, determining to again flash the first retinal region to recapture the first retinal image.
10. The computer program product of claim 8 , wherein capturing the first retinal image includes capturing a multi-frame video while the first retinal region is illuminated from the flashing, the flashing caused by a single flash, each frame of the multi-frame video capturing an image at a different level of flash exposure.
11. The computer program product of claim 8 , wherein determining that the first portion of the first retinal image does not meet the quality criterion comprises determining that the first portion of the first retinal image is either over-exposed or under-exposed.
12. The computer program product of claim 8 , wherein the second retinal image is an image of the retina of a same eye that the first retinal image depicts.
13. The computer program product of claim 8 , wherein performing a diagnosis using the plurality of retinal images comprises:
generating a composite image comprising the first portion of the first retinal image with the second portion of the second retinal image stitched into the first retinal image; and
performing the diagnosis using the composite image.
14. The computer program product of claim 8 , wherein performing a diagnosis using the plurality of retinal images comprises:
analyzing the first retinal image while discounting the first portion depicted in the first retinal image to generate a first analysis;
analyzing the second portion of the second retinal image to generate a second analysis; and
performing the diagnosis using the first analysis and the second analysis.
15. A system for minimizing exposure of a retina to flash during image gathering for diagnosis, the system comprising:
memory with instructions encoded thereon; and
one or more processors that, when executing the instructions, are caused to perform operations comprising:
capturing a first retinal image of a first retinal region by flashing the first retinal region responsive to determining a capturing device is focused on the first retinal region;
capturing a second retinal image of a second retinal region by flashing the second retinal region, the first retinal image and the second retinal image together forming a plurality of retinal images;
determining whether to again flash the first retinal region by:
determining that a first portion of the retina depicted in the first retinal image does not meet a quality criterion;
responsive to determining that the first portion of the retina does not meet the quality criterion, determining whether the first portion of the retina is depicted in a second portion of the second retinal image;
responsive to determining that the first portion of the retina is depicted in the second portion of the second retinal image, determining whether a depiction of the first portion of the retina in the second portion meets the quality criterion; and
responsive to determining that the depiction in the second portion meets the quality criterion, determining not to again flash the first retinal region; and
passing the plurality of retinal images to a fully autonomous machine learning model that outputs a likelihood of a disease condition based on the plurality of retinal images.
16. The system of claim 15 , the operations further comprising, responsive to determining that the second portion does not meet the quality criterion, determining to again flash the first retinal region to recapture the first retinal image.
17. The system of claim 15 , wherein capturing the first retinal image includes capturing a multi-frame video while the first retinal region is illuminated from the flashing, the flashing caused by a single flash, each frame of the multi-frame video capturing an image at a different level of flash exposure.
18. The system of claim 15 , wherein determining that the first portion of the first retinal image does not meet the quality criterion comprises determining that the first portion of the first retinal image is either over-exposed or under-exposed.
19. The system of claim 15 , wherein the second retinal image is an image of the retina of a same eye that the first retinal image depicts.
20. The system of claim 15 , wherein performing a diagnosis using the plurality of retinal images comprises:
generating a composite image comprising the first portion of the first retinal image with the second portion of the second retinal image stitched into the first retinal image; and
performing the diagnosis using the composite image.