公开(公告)号：US20220301152A1

公开(公告)日：2022-09-22

申请号：US17257999

申请日：2020-08-17

Applicant: Google LLC

Inventor： Jason Yim ,  Reena Kumari Chopra ,  Terry Spitz ,  Jim Huibrecht Winkens ,  Annette Ada Nkechinyere Obika ,  Trevor Back ,  Joseph R. Ledsam ,  Pearse A. Keane ,  Jeffrey De Fauw

IPC: G06T7/00 ,  G06V10/764 ,  G06V10/82 ,  G06T7/11 ,  A61B5/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a final progression score characterizing a likelihood that a state of a medical condition affecting eye tissue will progress to a target state in a future interval of time. In one aspect, a method comprises: obtaining: (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; providing the input image to each of one or more first classification neural networks to obtain a respective first progression score from each first classification neural network; providing the segmentation map to each of one or more 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 the first and second progression scores.

公开(公告)号：US11935232B2

公开(公告)日：2024-03-19

申请号：US17257999

申请日：2020-08-17

Applicant: Google LLC

Inventor： Jason Yim ,  Reena Kumari Chopra ,  Terry Spitz ,  Jim Huibrecht Winkens ,  Annette Ada Nkechinyere Obika ,  Trevor Back ,  Joseph R. Ledsam ,  Pearse A. Keane ,  Jeffrey De Fauw

IPC: A61B5/00 ,  G06T7/00 ,  G06T7/11 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06T7/0012 ,  A61B5/4842 ,  A61B5/7275 ,  G06T7/11 ,  G06V10/764 ,  G06V10/82 ,  G06T2200/04 ,  G06T2207/10012 ,  G06T2207/10101 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30041 ,  G06V2201/03

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a final progression score characterizing a likelihood that a state of a medical condition affecting eye tissue will progress to a target state in a future interval of time. In one aspect, a method comprises: obtaining: (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; providing the input image to each of one or more first classification neural networks to obtain a respective first progression score from each first classification neural network; providing the segmentation map to each of one or more 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 the first and second progression scores.