Semi-automatic muscle segmentation in MR images using deep registration-based label propagation-Reference-Cited by-同舟云学术

Semi-automatic muscle segmentation in MR images using deep registration-based label propagation

Published:2023-08 Issue: Volume:140 Page:109529
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Decaux Nathan^ORCID,Conze Pierre-Henri,Ropars Juliette,He Xinyan,Sheehan Frances T.,Pons Christelle,Ben Salem Douraied,Brochard Sylvain,Rousseau François

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference31 articles.

1. Reproducibility of manual segmentation in muscle imaging;Muzic;Acta Myol.,2021

2. Mathematical textbook of deformable neuroanatomies;Miller;Proc. Natl. Acad. Sci.,1993

3. ScribbleNet: efficient interactive annotation of urban city scenes for semantic segmentation;Sambaturu;Pattern Recognit.,2023

4. A supervised patch-based approach for human brain labeling;Rousseau;IEEE Trans. Med. Imaging,2011

5. Overview of MR image segmentation strategies in neuromuscular disorders;Ogier;Front. Neurol.,2021

Cited by 4 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. Weighted window attention and recover feature resolution-based network for deformable abdominal image registration;Biomedical Signal Processing and Control;2024-09

2. Cross co-teaching for semi-supervised medical image segmentation;Pattern Recognition;2024-08

3. Prediction of preoperative microvascular invasion by dynamic radiomic analysis based on contrast-enhanced computed tomography;Abdominal Radiology;2023-12-05

4. Current and Emerging Trends in Medical Image Segmentation With Deep Learning;IEEE Transactions on Radiation and Plasma Medical Sciences;2023-07