Evolving graph convolutional network with transformer for CT segmentation
-
Published:2024-11
Issue:
Volume:165
Page:112069
-
ISSN:1568-4946
-
Container-title:Applied Soft Computing
-
language:en
-
Short-container-title:Applied Soft Computing
Author:
Cui HuiORCID,
Jin Qiangguo,
Wu Xixi,
Wang Linlin,
Zhang Tiangang,
Nakaguchi Toshiya,
Xuan PingORCID,
Feng David Dagan
Reference43 articles.
1. 3D U-net: Learning dense volumetric segmentation from sparse annotation;Çiçek,2016
2. nnU-Net: A self-configuring method for deep learning-based biomedical image segmentation;Isensee;Nat. Methods,2021
3. The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge;Heller;Med. Image Anal.,2021
4. RA-unet: A hybrid deep attention-aware network to extract liver and tumor in CT scans;Jin;Front. Bioeng. Biotechnol.,2020
5. H. Zhao, J. Shi, X. Qi, X. Wang, J. Jia, Pyramid scene parsing network, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 2881–2890.