C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation-Reference-Cited by-同舟云学术

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C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation

Published:2020-06 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Yu Qihang,Yang Dong,Roth Holger,Bai Yutong,Zhang Yixiao,Yuille Alan L.,Xu Daguang

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9142308/9156271/09156654.pdf?arnumber=9156654

Cited by 112 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MSA-Net: Multi-scale feature fusion network with enhanced attention module for 3D medical image segmentation;Computers and Electrical Engineering;2024-12

2. Universal and extensible language-vision models for organ segmentation and tumor detection from abdominal computed tomography;Medical Image Analysis;2024-10

3. DIPO: Differentiable Parallel Operation Blocks for Surgical Neural Architecture Search;IEEE Journal of Biomedical and Health Informatics;2024-09

4. A deep learning-based cascade algorithm for pancreatic tumor segmentation;Frontiers in Oncology;2024-08-07

5. SSCFormer: Revisiting ConvNet-Transformer Hybrid Framework From Scale-Wise and Spatial-Channel-Aware Perspectives for Volumetric Medical Image Segmentation;IEEE Journal of Biomedical and Health Informatics;2024-08

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