Patent ID: 11935232
Assignee: GOOGLE LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G  A | IPC A  G

Claim 0:
1. A system comprising:
one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to implement:
one or more first classification neural networks, wherein each first classification neural network is configured to:
receive, by an input layer of the first classification neural network, an image of eye tissue captured using an imaging modality; and
process the image to generate, by an output layer of the first classification neural network, a first progression score characterizing a likelihood that a state of a medical condition affecting the eye tissue will progress to a target state in a future interval of time;

one or more second classification neural networks, wherein each second classification neural network is configured to:
receive, by an input layer of the second classification neural network, a segmentation map of an image of eye tissue that segments the eye tissue in the image into a plurality of tissue types; and
process the segmentation map to generate, by an output layer of the second classification neural network, a second progression score characterizing a likelihood that a state of a medical condition affecting the eye tissue will progress to a target state in a future interval of time;

a subsystem configured to:
obtain: (i) an input image of eye tissue captured using an imaging modality, and (ii) a segmentation map of the eye tissue in the input image into a plurality of tissue types; and
generate, based on the input image and the segmentation map, a final progression score characterizing a likelihood that a state of a medical condition affecting the eye tissue will progress to a target state in a future interval of time, comprising:
providing the input image to each of the first classification neural networks to obtain a respective first progression score from each first classification neural network;
providing the segmentation map to each of the second classification neural networks to obtain a respective second progression score from each second classification neural network; and
generating the final progression score based on: (i) the first progression scores obtained based on the input image of eye tissue, and (ii) the second progression scores obtained based on the segmentation map.