Self-supervised learning methods and applications in medical imaging analysis: a survey

• Published in: PeerJ. Computer science Vol. 8; p. e1045
• Main Authors: Shurrab, Saeed, Duwairi, Rehab
• Format: Journal Article
• Language: English
• Published: United States PeerJ. Ltd 19.07.2022; PeerJ, Inc; PeerJ Inc
• Subjects: Annotations; Artificial Intelligence; Bioinformatics; Computer Vision; Contrastive Learning; Data Mining and Machine Learning; Data Science; Datasets; Deep learning; Human performance; Imaging Modality; Localization; Machine learning; Machine vision; Medical advice systems; Medical imaging; Medical imaging equipment; Pretext Task; Self-Supervised Learning; State-of-the-art reviews; Surveys; Contrastive Learning; Pretext Task; Imaging Modality; Self-Supervised Learning; Medical-Imaging

The scarcity of high-quality annotated medical imaging datasets is a major problem that collides with machine learning applications in the field of medical imaging analysis and impedes its advancement. Self-supervised learning is a recent training paradigm that enables learning robust representation...