公开(公告)号：US20230025980A1

公开(公告)日：2023-01-26

申请号：US17782497

申请日：2020-12-04

Applicant: Genentech, Inc.

Inventor： Michael Gregg KAWCZYNSKI ,  Jeffrey R. WILLIS ,  Nils Gustav Thomas BENGTSSON ,  Jian DAI ,  Simon Shang GAO

IPC: G06T7/00 ,  G06T3/00 ,  G06T7/187

Abstract: Systems and methods relate to processing optical tomography coherence (OCT) images to predict characteristics of a treatment to be administered to effectively treat age-related macular degeneration. The processing can include pre-processing the image by flattening and/or cropping the image and processing the pre-processed image using a neural network. The neural network can include a deep convolutional neural network. An output of the neural network can indicate a predicted frequency and/or interval at which a treatment (e.g., anti-vascular endothelial growth factor therapy) is to be administered so as to prevent leakage of vasculature in the eye.

公开(公告)号：US20240038370A1

公开(公告)日：2024-02-01

申请号：US18482237

申请日：2023-10-06

Applicant: Genentech, Inc.

Inventor： Neha Sutheekshna ANEGONDI ,  Jian DAI ,  Michael Gregg KAWCZYNSKI ,  Yusuke Alexander KIKUCHI

IPC: G16H30/40 ,  G16H10/60 ,  G06T7/00

CPC classification number: G16H30/40 ,  G16H10/60 ,  G06T7/0012 ,  G06T2207/30041 ,  G06T2207/10101 ,  G06T2207/20081

Abstract: A method and system for predicting a treatment outcome. Three-dimensional imaging data for a retina of a subject is received. A first output is generated using a deep learning system and the three-dimensional imaging data. The first output and baseline data are received as input for a symbolic model. A treatment outcome is predicted, via the symbolic model, for the subject undergoing a treatment for neovascular age-related macular degeneration (nAMD) using the input.

公开(公告)号：US20230342935A1

公开(公告)日：2023-10-26

申请号：US18304006

申请日：2023-04-20

Applicant: Genentech, Inc.

Inventor： Neha Sutheekshna ANEGONDI ,  Simon Shang GAO ,  Jiaxiang JIANG ,  Michael Gregg KAWCZYNSKI ,  Jasmine PATIL ,  Theodore C. SPAIDE

IPC: G06T7/00 ,  G06T7/174 ,  G06T7/62 ,  A61B3/10 ,  A61B3/12

CPC classification number: G06T7/0014 ,  G06T7/174 ,  G06T7/62 ,  A61B3/102 ,  A61B3/1225 ,  G06T2207/10064 ,  G06T2207/10048 ,  G06T2207/10101 ,  G06T2207/30041 ,  G06T2207/30096 ,  G06T2207/20084 ,  G06T2207/20021

Abstract: A method and system for generating a geographic atrophy (GA) lesion segmentation mask corresponding to GA lesions in a retina is disclosed herein. In some embodiments, a set of fundus autofluorescence (FAF) images of a retina having one or more geographic atrophy (GA) lesions and one or both of a set of infrared (IR) images of the retina or a set of optical coherence tomography (OCT) images of the retina may be used to generate the GA lesion segmentation mask including one or more GA lesion segments corresponding to the one or more GA lesions in the retina. In some instances, a neural network may be used to generate the GA lesion segmentation mask.