Medical Image Segmentation based on Multi-Perception Field Feature Interaction

Author:

Jing Wanting1ORCID,Gai Jiale1ORCID,Zhu Minghui1ORCID,Kang Jialong1ORCID,Cheng Dapeng1ORCID

Affiliation:

1. Shandong Technology and Business University, China

Publisher

ACM

Reference15 articles.

1. Ronneberger O, Fischer P, Brox T. U-net: Convolutional networks for biomedical image segmentation[C]//Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 18. Springer International Publishing, 2015: 234-241.

2. Chen J, Lu Y, Yu Q, Transunet: Transformers make strong encoders for medical image segmentation[J]. arXiv preprint arXiv:2102.04306, 2021.

3. Transformers in medical image segmentation: A review

4. Oktay O, Schlemper J, Folgoc L L, Attention u-net: Learning where to look for the pancreas. arXiv 2018[J]. arXiv preprint arXiv:1804.03999, 1804.

5. TransAttUnet: Multi-Level Attention-Guided U-Net With Transformer for Medical Image Segmentation

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