Multi-instance discriminative contrastive learning for brain image representation

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...

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Vydáno v:	Neural computing & applications Ročník 37; číslo 11; s. 7459 - 7472
Hlavní autoři:	Zhang, Yupei, Liu, Shuhui, Qu, Xiran, Shang, Xuequn
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Springer London 01.04.2025 Springer Nature B.V
Témata:	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
ISSN:	0941-0643, 1433-3058
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