Cats: Complementary CNN and Transformer Encoders for Segmentation. (arXiv:2208.11572v1 [eess.IV])

Recently, deep learning methods have achieved state-of-the-art performance in
many medical image segmentation tasks. Many of these are based on convolutional
neural networks (CNNs). For such methods, the encoder is the key part for
global and local information extraction from input images; the extracted
features are then passed to the decoder for predicting the segmentations. In
contrast, several recent works show a superior performance with the use of
transformers, which can better model long-range spatial dependencies and
capture low-level details. …

arxiv cats cnn segmentation transformer