Diffusion Model Based Semi-supervised Learning on Brain Hemorrhage Images for Efficient Midline Shift Quantification-Reference-Cited by-同舟云学术

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Diffusion Model Based Semi-supervised Learning on Brain Hemorrhage Images for Efficient Midline Shift Quantification

Published:2023 Issue: Volume: Page:69-81
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Gong Shizhan^ORCID,Chen Cheng^ORCID,Gong Yuqi^ORCID,Chan Nga Yan^ORCID,Ma Wenao^ORCID,Mak Calvin Hoi-Kwan^ORCID,Abrigo Jill^ORCID,Dou Qi^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-34048-2_6

Reference21 articles.

1. Caceres, J.A., Goldstein, J.N.: Intracranial hemorrhage. Emerg. Med. Clin. North Am. 30(3), 771 (2012)

2. Quattrocchi, K.B., et al.: Quantification of midline shift as a predictor of poor outcome following head injury. Surg. Neurol. 35(3), 183–188 (1991)

3. Yang, W.-S., Li, Q., Li, R., Liu, Q.-J., Wang, X.-C., et al.: Defining the optimal midline shift threshold to predict poor outcome in patients with supratentorial spontaneous intracerebral hemorrhage. Neurocrit. Care 28(3), 314–321 (2017). https://doi.org/10.1007/s12028-017-0483-7

4. Liao, C., Chen, Y., Xiao, F.: Brain midline shift measurement and its automation: a review of techniques and algorithms. Int. J. Biomed. Imaging, 4303161 (2018)

5. Lecture Notes in Computer Science;M Pisov,2019

Cited by 2 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. A Survey on Generative Diffusion Models;IEEE Transactions on Knowledge and Data Engineering;2024-07

2. Medical Image Segmentation of Intracranial Hemorrhage: A Review;2023 7th Asian Conference on Artificial Intelligence Technology (ACAIT);2023-11-10

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