Transformers-based architectures for stroke segmentation: A review

arXiv:2403.18637v1 Announce Type: cross
Abstract: Stroke remains a significant global health concern, necessitating precise and efficient diagnostic tools for timely intervention and improved patient outcomes. The emergence of deep learning methodologies has transformed the landscape of medical image analysis. Recently, Transformers, initially designed for natural language processing, have exhibited remarkable capabilities in various computer vision applications, including medical image analysis. This comprehensive review aims to provide an in-depth exploration of the cutting-edge Transformer-based architectures applied in the context of stroke …

abstract analysis architectures arxiv capabilities cs.cv cs.lg deep learning diagnostic eess.iv emergence global global health health image landscape language language processing medical natural natural language natural language processing patient processing review segmentation stroke tools transformers type