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What is Transformer Models in Medical Segmentation about?

This review discusses the advancements in medical image segmentation through the application of Transformer models, highlighting their superiority over traditional methods in handling complex medical images. It categorizes various Transformer architectures, such as Vision Transformer, Swin Transformer, and Pyramid Vision Transformer, and their specific applications in tasks like brain tumor and polyp segmentation. The review also addresses challenges in benchmarking these models and provides insights into c

Author

İsmail Kayadibi

Language

EN