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连续时间随机步行和分数顺序微积分模型的比较,用于描述乳腺病变,使用历史图分析

Caili Tang1, Feng Li2, Litong He1

  • 1Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.

Magnetic resonance imaging
|February 2, 2024
PubMed
概括

与空间和时间异质性参数相比,扩散系数参数在区分良性和恶性乳腺病变方面表现出优异的诊断性能. 全瘤组图分析有助于乳腺病变的表征.

关键词:
乳腺病变的病变 乳腺病变连续时间随机步行 (CTRW)扩散权重成像 (DWI) 的使用分数顺序运算 (FROC) 的计算方法历史图分析分析 历史图分析

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