公开(公告)号：US20230326022A1

公开(公告)日：2023-10-12

申请号：US18297281

申请日：2023-04-07

申请人： Bristol-Myers Squibb Company ,  PathAI, Inc.

发明人： Vanessa Matos-Cruz ,  George Lee ,  Varsha Chinnaobireddy ,  Maryam Pouryahya ,  Darren Thomas Fahy ,  Christian Winskell Kirkup ,  Kathleen Sucipto ,  Sai Chowdary Gullapally ,  Archit Khosla ,  Nishant Agrawal ,  Benjamin Patrick Glass ,  Sergine Brutus ,  Limin Yu ,  Murray Berle Resnick ,  Rachel L. Sargent ,  Vipul Atulkumar Baxi ,  Scott Ely ,  Benjamin J. Chen

IPC分类号： G06T7/00 ,  G06V20/69 ,  G06V10/774 ,  G06V10/82 ,  G16H30/40 ,  G16H50/20 ,  G16H20/10

CPC分类号： G06T7/0012 ,  G06V20/698 ,  G06V10/774 ,  G06V10/82 ,  G06V20/695 ,  G16H30/40 ,  G16H50/20 ,  G16H20/10 ,  G06T2207/20036 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06V2201/03 ,  G06T2207/30096

摘要： A method includes receiving an input histology image, processing, using a cell classification model, the input histology image to generate one or more lymphocyte density maps within the input histology image, and performing morphological image processing on the one or more lymphocyte density maps to identify one or more TLS regions within the input histology image. Each TLS region is represented by a respective cluster of lymphocyte cells. For each corresponding TLS region of the one or more TLS regions identified in the input histology image, the method also includes extracting, from the respective cluster of lymphocyte cells, a respective set of TLS features, and processing, using a TLS classification model, the respective set of TLS features to classify the corresponding TLS region as one of a first TLS maturation state, a second TLS maturation state, or a third TLS maturation state.