Invention Publication
- Patent Title: PREDICTING GEOGRAPHIC ATROPHY GROWTH RATE FROM FUNDUS AUTOFLUORESCENCE IMAGES USING DEEP NEURAL NETWORKS
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Application No.: US18153762Application Date: 2023-01-12
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Publication No.: US20230154595A1Publication Date: 2023-05-18
- Inventor: Simon Shang GAO , Neha Sutheekshna ANEGONDI
- Applicant: Genentech, Inc.
- Applicant Address: US CA South San Francisco
- Assignee: Genentech, Inc.
- Current Assignee: Genentech, Inc.
- Current Assignee Address: US CA South San Francisco
- Main IPC: G16H30/40
- IPC: G16H30/40 ; G16H50/20
Abstract:
A method and system for evaluating geographic atrophy in a retina. A set of fundus autofluorescence (FAF) images of the retina is received. An input is generated for a machine learning system using the set of fundus autofluorescence images. A lesion area is predicted, via the machine learning system, for the geographic atrophy lesion in the retina using the set of fundus autofluorescence images. A lesion growth rate is predicted, via the machine learning system, for the geographic atrophy lesion in the retina using the input.
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