Invention Publication
- Patent Title: SYSTEMS, METHODS, AND APPARATUSES FOR IMPLEMENTING PATCH ORDER PREDICTION AND APPEARANCE RECOVERY (POPAR) BASED IMAGE PROCESSING FOR SELF-SUPERVISED LEARNING MEDICAL IMAGE ANALYSIS
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Application No.: US18241809Application Date: 2023-09-01
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Publication No.: US20240078666A1Publication Date: 2024-03-07
- Inventor: Jiaxuan PANG , Fatemeh Haghighi , DongAo Ma , Nahid Ui Islam , Mohammad Reza Hosseinzadeh Taher , Jianming Liang
- Applicant: Arizona Board of Regents on behalf of Arizona State University
- Applicant Address: US AZ Scottsdale
- Assignee: Arizona Board of Regents on behalf of Arizona State University
- Current Assignee: Arizona Board of Regents on behalf of Arizona State University
- Current Assignee Address: US AZ Scottsdale
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G06T7/11 ; G06V10/54 ; G16H30/40

Abstract:
A self-supervised machine learning method and system for learning visual representations in medical images. The system receives a plurality of medical images of similar anatomy, divides each of the plurality of medical images into its own sequence of non-overlapping patches, wherein a unique portion of each medical image appears in each patch in the sequence of non-overlapping patches. The system then randomizes the sequence of non-overlapping patches for each of the plurality of medical images, and randomly distorts the unique portion of each medical image that appears in each patch in the sequence of non-overlapping patches for each of the plurality of medical images. Thereafter, the system learns, via a vision transformer network, patch-wise high-level contextual features in the plurality of medical images, and simultaneously, learns, via the vision transformer network, fine-grained features embedded in the plurality of medical images.
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