Transformer-based approaches for neuroimaging: an in-depth review of their role in classification and regression tasks
Xinyu Zhu,
Shen Sun,
Lan Lin
et al.
Abstract:In the ever-evolving landscape of deep learning (DL), the transformer model emerges as a formidable neural network architecture, gaining significant traction in neuroimaging-based classification and regression tasks. This paper presents an extensive examination of transformer’s application in neuroimaging, surveying recent literature to elucidate its current status and research advancement. Commencing with an exposition on the fundamental principles and structures of the transformer model and its variants, thi… Show more
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