Overview of the typical SSL pipeline for neuroimaging data analysis (IMAGE)
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The top represents the brain network pipeline, where raw neurological data is systematically processed to extract meaningful representations. The bottom highlights the core self-supervised model, comprising an encoder-decoder architecture. These refined representations are then utilized for downstream tasks, such as disease categorization, detection, and prediction. The model's bidirectional learning flow ensures robustness and adaptability across diverse neuroimaging datasets.
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Harbin Institute of Technology, Shenzhen
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