Title:
DISSIMILAR-PAIRED NEURAL NETWORK ARCHITECTURE FOR DATA SEGMENTATION
Document Type and Number:
WIPO Patent Application WO/2022/111546
Kind Code:
A1
Abstract:
A computer-implemented system (CIS) is provided for processing and/or analyzing non-contrast-enhance computer tomography medical imaging input data is described. The CIS contains (i) twin U-Net architectures with equal weights, which are built on a Siamese architecture, and (ii) a Dissimilar block operably linked to the two U-Net architectures, and built on top of the Siamese-U-Net architecture to form a Dissimilar-Siamese-U-Net architecture. The computer-implemented system can be used in diagnosing acute ischemic stroke and/or thromoboembolus, by analyzing separate and independent input images of the left and right hemispheres of a brain. The diagnosis is based on a detection of the presence of a hyperdense middle cerebral artery sign.
Inventors:
YU PHILIP LEUNG HO (CN)
YOU JIA (CN)
TSANG ANDERSON CHUN ON (CN)
LEUNG GILBERTO KA KIT (CN)
YOU JIA (CN)
TSANG ANDERSON CHUN ON (CN)
LEUNG GILBERTO KA KIT (CN)
Application Number:
PCT/CN2021/132919
Publication Date:
June 02, 2022
Filing Date:
November 24, 2021
Export Citation:
Assignee:
UNIV HONG KONG (CN)
International Classes:
G06N3/04
Foreign References:
| CN111724397A | 2020-09-29 | |||
| US20120114205A1 | 2012-05-10 |
Other References:
AAKASH AGRAWAL: "Dissimilarity learning via Siamese network predicts brain imaging data", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 1 July 2019 (2019-07-01), 201 Olin Library Cornell University Ithaca, NY 14853 , XP081438278
Attorney, Agent or Firm:
LIU, SHEN & ASSOCIATES (CN)
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