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C2FTrans: Coarse-to-Fine Transformers for Medical Image Segmentation
[article]
2022
arXiv
pre-print
Convolutional neural networks (CNN), the most prevailing architecture for deep-learning based medical image analysis, are still functionally limited by their intrinsic inductive biases and inadequate receptive fields. Transformer, born to address this issue, has drawn explosive attention in natural language processing and computer vision due to its remarkable ability in capturing long-range dependency. However, most recent transformer-based methods for medical image segmentation directly apply
arXiv:2206.14409v2
fatcat:gfmmolmiefbnhbsruu2nezba2e