Multi-instance discriminative contrastive learning for brain image representation

• Published in: Neural computing & applications Vol. 37; no. 11; pp. 7459 - 7472
• Main Authors: Zhang, Yupei, Liu, Shuhui, Qu, Xiran, Shang, Xuequn
• Format: Journal Article
• Language: English
• Published: London Springer London 01.04.2025; Springer Nature B.V
• Subjects: Artificial Intelligence; Brain; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Data Mining and Knowledge Discovery; Image classification; Image Processing and Computer Vision; Learning; Magnetic resonance imaging; Medical imaging; Neuroimaging; Probability and Statistics in Computer Science; Representations; S.I.: Efficient Artificial Intelligent Algorithms for Medical Image Analysis Based on High-Performance Computing; Special Issue on Efficient Artificial Intelligent Algorithms for Medical Image Analysis Based on High-Performance Computing; Deep learning; Education impacts; Multi-instance contrastive learning; NeuroImage analysis; Brain learning Development; MRI classification

This paper focuses on the problem of learning discriminative representation for brain images, which is a critical task toward understanding brain developments. Related studies usually extract manual and statistical features from the functional magnetic resonance images (MRIs) to differentiate brain...