Invention Grant
- Patent Title: Medical scan image analysis system
-
Application No.: US16420460Application Date: 2019-05-23
-
Publication No.: US10748652B2Publication Date: 2020-08-18
- Inventor: Li Yao , Devon Bernard , Kevin Lyman , Diogo Almeida , Jeremy Howard
- Applicant: Enlitic, Inc.
- Applicant Address: US CA San Francisco
- Assignee: Enlitic, Inc.
- Current Assignee: Enlitic, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Garlick & Markison
- Agent Bruce E. Stuckman
- Main IPC: G16H30/40
- IPC: G16H30/40 ; G06F19/00 ; G06F3/048 ; G06T7/00 ; G06Q50/22 ; G16H50/20 ; A61B6/00 ; A61B8/00 ; A61B8/08 ; G16H50/70 ; G06N3/04 ; G06F40/30 ; G06F40/56 ; G06F40/169 ; G06F40/197 ; G06F40/247 ; G06F40/279 ; G16H30/20 ; G16H10/60 ; G16H15/00 ; G16H50/30 ; A61B6/03 ; G06F3/16 ; G06K9/03 ; G06K9/62 ; A61B5/00 ; G06N3/08 ; G16H40/20 ; G06Q10/10 ; G06T7/11 ; G01T1/24 ; H04N5/32 ; G16H40/63 ; G06T11/60 ; G06N20/10 ; G06N7/00 ; G16H50/50 ; H04L29/08 ; H04L29/06 ; G06F3/0484 ; G06F3/0485 ; G06T11/00

Abstract:
A medical scan image analysis system is operable to receive a plurality of medical scans that represent a three-dimensional anatomical region and include a plurality of cross-sectional image slices. A plurality of three-dimensional subregions corresponding to each of the plurality of medical scans are generated by selecting a proper subset of the plurality of cross-sectional image slices from each medical scan, and by further selecting a two-dimensional subregion from each proper subset of cross-sectional image slices. A learning algorithm is performed on the plurality of three-dimensional subregions to generate a fully convolutional neural network. Inference data corresponding to a new medical scan received via the network is generated by performing an inference algorithm on the new medical scan by utilizing the fully convolutional neural network. An inferred abnormality is identified in the new medical scan based on the inference data.
Public/Granted literature
- US20190279760A1 MEDICAL SCAN IMAGE ANALYSIS SYSTEM Public/Granted day:2019-09-12
Information query