Invention Grant
- Patent Title: Anatomy segmentation through low-resolution multi-atlas label fusion and corrective learning
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Application No.: US16363330Application Date: 2019-03-25
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Publication No.: US10410384B2Publication Date: 2019-09-10
- Inventor: Hongzhi Wang
- 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 Stephen Kenny; Erik Huestis
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06T11/00 ; G06K9/62 ; G06K9/66 ; G06T7/11 ; G06T7/30 ; A61B6/03

Abstract:
Computationally efficient anatomy segmentation through low-resolution multi-atlas label fusion and corrective learning is provided. In some embodiments, an input image is read. The input image has a first resolution. The input image is downsampled to a second resolution lower than the first resolution. The downsampled image is segmented into a plurality of labeled anatomical segments. Error correction is applied to the segmented image to generate an output image. The output image has the first resolution.
Public/Granted literature
- US20190221014A1 ANATOMY SEGMENTATION THROUGH LOW-RESOLUTION MULTI-ATLAS LABEL FUSION AND CORRECTIVE LEARNING Public/Granted day:2019-07-18
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