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Updated: May 5, 2026

Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models
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肺叶细分:与本地内部模型相比,开源MOOSE,TotalSegmentator和LungMask模型的性能

Elaheh Amini1, Ran Klein2,3,4

  • 1Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada. eamini@ohri.ca.

European radiology experimental
|September 4, 2025
PubMed
概括

对于肺叶细分的深度学习模型在常见病例上表现良好, 用多样化,代表性的数据集进行培训可以提高准确性,特别是在具有挑战性的肺部疾病中.

关键词:
数据的可变性深度学习图像处理 (细分)肺部断层扫描 (X射线计算)

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