Invention Application
- Patent Title: MULTIMODALITY IMAGE PROCESSING TECHNIQUES FOR TRAINING IMAGE DATA GENERATION AND USAGE THEREOF FOR DEVELOPING MONO-MODALITY IMAGE INFERENCING MODELS
-
Application No.: US17093960Application Date: 2020-11-10
-
Publication No.: US20220101048A1Publication Date: 2022-03-31
- Inventor: Tao Tan , Gopal B. Avinash , Máté Fejes , Ravi Soni , Dániel Attila Szabó , Rakesh Mullick , Vikram Melapudi , Krishna Seetharam Shriram , Sohan Rashmi Ranjan , Bipul Das , Utkarsh Agrawal , László Ruskó , Zita Herczeg , Barbara Darázs
- Applicant: GE Precision Healthcare LLC
- Applicant Address: US WI Milwaukee
- Assignee: GE Precision Healthcare LLC
- Current Assignee: GE Precision Healthcare LLC
- Current Assignee Address: US WI Milwaukee
- Priority: IN202041042184 20200929
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06T5/50 ; G06T7/30 ; G06N5/04 ; G16H30/20 ; G16H30/40 ; G16H50/20 ; G16H50/50 ; A61B6/03 ; A61B6/00 ; A61B5/055 ; A61B5/00

Abstract:
Techniques are described for generating mono-modality training image data from multi-modality image data and using the mono-modality training image data to train and develop mono-modality image inferencing models. A method embodiment comprises generating, by a system comprising a processor, a synthetic 2D image from a 3D image of a first capture modality, wherein the synthetic 2D image corresponds to a 2D version of the 3D image in a second capture modality, and wherein the 3D image and the synthetic 2D image depict a same anatomical region of a same patient. The method further comprises transferring, by the system, ground truth data for the 3D image to the synthetic 2D image. In some embodiments, the method further comprises employing the synthetic 2D image to facilitate transfer of the ground truth data to a native 2D image captured of the same anatomical region of the same patient using the second capture modality.
Public/Granted literature
Information query