Multimodal MRI segmentation of key structures for microvascular decompression via knowledge-driven mutual distillation and topological constraints-Reference-Cited by-同舟云学术

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Multimodal MRI segmentation of key structures for microvascular decompression via knowledge-driven mutual distillation and topological constraints

Published:2024-05-13 Issue:7 Volume:19 Page:1329-1338
ISSN:1861-6429
Container-title:International Journal of Computer Assisted Radiology and Surgery
language:en
Short-container-title:Int J CARS

Author:

Tu Renzhe,Zhang Doudou,Li Caizi,Xiao Linxia,Zhang Yong,Cai Xiaodong,Si Weixin^ORCID

Funder

Research Grants Council of the Hong Kong Special Administrative Region

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

Shenzhen Fundamental Research Program

Key Technologies Research and Development Program of Guangzhou Municipality

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11548-024-03159-2.pdf

Reference22 articles.

1. Alonso I, Sabater A, Ferstl D, Montesano L, Murillo AC (2021) Semi-supervised semantic segmentation with pixel-level contrastive learning from a class-wise memory bank. In: Proceedings of the IEEE/CVF international conference on computer vision, pp. 8219–8228

2. Chen C, Dou Q, Jin Y, Liu Q, Heng PA (2021) Learning with privileged multimodal knowledge for unimodal segmentation. IEEE Trans Med Imaging 41(3):621–632

3. Clough JR, Byrne N, Oksuz I, Zimmer VA, Schnabel JA, King AP (2020) A topological loss function for deep-learning based image segmentation using persistent homology. IEEE Trans Pattern Anal Mach Intell 44(12):8766–8778

4. Dong C, Xu S, Dai D, Zhang Y, Zhang C, Li Z (2023) A novel multi-attention, multi-scale 3D deep network for coronary artery segmentation. Med Image Anal 85:102745

5. Hatamizadeh A, Nath V, Tang Y, Yang D, Roth HR, Xu D (2021) Swin unetr: swin transformers for semantic segmentation of brain tumors in MRI images. In: International MICCAI Brainlesion workshop, Springer, pp. 272–284

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