Editorial for “Collaborative Learning for Annotation‐Efficient Volumetric MR Image Segmentation”-Reference-Cited by-同舟云学术

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Editorial for “Collaborative Learning for Annotation‐Efficient Volumetric MR Image Segmentation”

Published:2024-01-23 Issue: Volume: Page:
ISSN:1053-1807
Container-title:Journal of Magnetic Resonance Imaging
language:en
Short-container-title:Magnetic Resonance Imaging

Author:

Sabati Mohammad¹²^ORCID,Yang Mingrui³,Chauhan Anil⁴

Affiliation:

1. Hoglund Biomedical Imaging Center University of Kansas Medical Center Kansas City Kansas USA

2. Bioengineering Program, School of Engineering University of Kansas Lawrence Kansas USA

3. Department of Biomedical Engineering, Program of Advanced Musculoskeletal Imaging Cleveland Clinic Cleveland Ohio USA

4. Department of Radiology University of Kansas Medical Center Kansas City Kansas USA

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jmri.29212

Reference10 articles.

1. Recent advances and clinical applications of deep learning in medical image analysis

2. Deep Learning for Lesion Detection, Progression, and Prediction of Musculoskeletal Disease

3. ZhouY HeX HuangL LiuL ZhuF CuiS ShaoL.Collaborative learning of semi‐supervised segmentation and classification for medical images. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Long Beach CA USA 2019 pp. 2074–2083.https://doi.org/10.1109/CVPR.2019.00218.

4. SCL-Net: Structured Collaborative Learning for PET/CT Based Tumor Segmentation

5. SSMD: Semi-Supervised medical image detection with adaptive consistency and heterogeneous perturbation

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