Invention Grant
- Patent Title: Cross-modality neural network transform for semi-automatic medical image annotation
-
Application No.: US15294289Application Date: 2016-10-14
-
Publication No.: US11195313B2Publication Date: 2021-12-07
- Inventor: Yufan Guo , Mehdi Moradi
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Foley Hoag, LLP
- Agent Erik Huestis; Stephen Kenny
- Main IPC: G06T11/60
- IPC: G06T11/60 ; G06N3/04 ; G06K9/46 ; G06K9/62 ; G06N3/08

Abstract:
A cross-modality neural network transform for semi-automatic medical image annotation is provided. In various embodiments, an input medical image is mapped to a first vector in a text vector space. The first vector corresponds to the features of the medical image. A set of predetermined vectors is searched for a closest one of the predetermined vectors to the first vector. From the closest one of the predetermined vectors, one or more keywords is determined describing the input medical image.
Public/Granted literature
- US20180108124A1 CROSS-MODALITY NEURAL NETWORK TRANSFORM FOR SEMI-AUTOMATIC MEDICAL IMAGE ANNOTATION Public/Granted day:2018-04-19
Information query