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Updated: Jan 22, 2026

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

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以边界意识和差异为指导的动态伪标签与一致性学习用于半监督的3D TOF-MRA脑血管细分的半监督3D TOF-MRA脑血管细分

Nazik Mohamad Ahmed Elsayed1, Jiarun Liu2, Cheng Li3

  • 1Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Shenzhen, 518055, CHINA.

Physics in medicine and biology
|January 20, 2026
PubMed
概括

这项研究介绍了BDD-CL,这是一个新的框架,用于在3D TOF-MRA扫描中进行半监督的大脑血管细分. 该方法提高了细分复杂血管结构的准确性和效率,有助于临床诊断.

关键词:
3D TOF-MRA 大脑血管细分提高边界意识的提升动态伪标签选择选择半监督学习 半监督学习形状意识的不一致性

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