公开(公告)号：US11817204B2

公开(公告)日：2023-11-14

申请号：US17116366

申请日：2020-12-09

Applicant: Case Western Reserve University

Inventor： Anant Madabhushi ,  Nathaniel Braman ,  Tristan Maidment ,  Yijiang Chen

IPC: G16H30/40 ,  G06T7/00 ,  A61B6/00 ,  A61B6/02 ,  G16H50/20 ,  G06N3/04 ,  G06T7/11 ,  G06F18/214 ,  G06V10/25 ,  G06V10/764 ,  G06V10/82

CPC classification number: G16H30/40 ,  A61B6/025 ,  A61B6/469 ,  A61B6/502 ,  A61B6/5217 ,  G06F18/214 ,  G06N3/04 ,  G06T7/0012 ,  G06T7/11 ,  G06V10/25 ,  G06V10/764 ,  G06V10/82 ,  G16H50/20 ,  G06T2207/10112 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30068 ,  G06T2207/30096 ,  G06V2201/03

Abstract: Embodiments discussed herein facilitate determination of whether lesions are benign or malignant. One example embodiment is a method, comprising: accessing medical imaging scan(s) that are each associated with distinct angle(s) and each comprise a segmented region of interest (ROI) of that medical imaging scan comprising a lesion associated with a first region and a second region; providing the first region(s) of the medical imaging scan(s) to trained first deep learning (DL) model(s) of an ensemble and the second region(s) of the medical imaging scan(s) to trained second DL model(s) of the ensemble; and receiving, from the ensemble of DL models, an indication of whether the lesion is a benign architectural distortion (AD) or a malignant AD.

公开(公告)号：US20210174504A1

公开(公告)日：2021-06-10

申请号：US17116366

申请日：2020-12-09

Applicant: Case Western Reserve University ,  Louis Stokes Cleveland Veterans Administration Medical Center

Inventor： Anant Madabhushi ,  Nathaniel Braman ,  Tristan Maidment ,  Yijiang Chen

IPC: G06T7/00 ,  G06T7/11 ,  G06K9/62 ,  A61B6/00 ,  A61B6/02 ,  G16H30/40 ,  G16H50/20 ,  G06N3/04

Abstract: Embodiments discussed herein facilitate determination of whether lesions are benign or malignant. One example embodiment is a method, comprising: accessing medical imaging scan(s) that are each associated with distinct angle(s) and each comprise a segmented region of interest (ROI) of that medical imaging scan comprising a lesion associated with a first region and a second region; providing the first region(s) of the medical imaging scan(s) to trained first deep learning (DL) model(s) of an ensemble and the second region(s) of the medical imaging scan(s) to trained second DL model(s) of the ensemble; and receiving, from the ensemble of DL models, an indication of whether the lesion is a benign architectural distortion (AD) or a malignant AD.