Cin-Seg: Causal Invariance for Tag-Supervised Segmentation on Medical Images-Reference-Cited by-同舟云学术

Cin-Seg: Causal Invariance for Tag-Supervised Segmentation on Medical Images

Published:2024 Issue: Volume:73 Page:1-13
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Chen Zhang¹^ORCID,Tian Zhiqiang¹^ORCID,Zhu Jihua¹^ORCID,Du Shaoyi²^ORCID,Sun Qindong³^ORCID

Affiliation:

1. School of Software, Xi’an Jiaotong University, Xi’an, China

2. National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, National Engineering Research Center for Visual Information and Applications, and Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China

3. School of Cyber Science and Engineering, Xi’an Jiaotong University, Xi’an, China

Funder

National Natural Science Foundation of China

Key Research and Development Program of Shaanxi Province of China

Natural Science Basic Research Plan in Shaanxi Province of China

Social Science Foundation of Shaanxi Province of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10530169.pdf?arnumber=10530169

Reference67 articles.

1. MRSCFusion: Joint Residual Swin Transformer and Multiscale CNN for Unsupervised Multimodal Medical Image Fusion

2. DRT: Deformable Region-Based Transformer for Nonrigid Medical Image Registration With a Constraint of Orientation

3. Two-Stage Convolutional Neural Network for Medical Noise Removal via Image Decomposition

4. DS-TransUNet: Dual Swin Transformer U-Net for Medical Image Segmentation

5. Fully convolutional networks for semantic segmentation