峰度
公制(单位)
磁共振弥散成像
帕金森病
医学
扩散成像
模式识别(心理学)
人工智能
计算机科学
放射科
数学
疾病
磁共振成像
统计
病理
工程类
运营管理
作者
N Zhang,Wei Zhao,Song’an Shang,Hongying Zhang,Xiang Lv,Lanlan Chen,Weiqiang Dou,Jing Ye
标识
DOI:10.1016/j.acra.2024.07.001
摘要
Parkinson's disease (PD) shows small structural changes in nigrostriatal pathways, which can be sensitively captured through diffusion kurtosis imaging (DKI). However, the value of DKI and its radiomic features in the classification performance of PD still need confirmation. This study aimed to compare the diagnostic efficiency of DKI-derived kurtosis metric and its radiomic features with different machine learning models for PD classification.
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