| 祁纳,赵军.基于MRI影像组学和机器学习诊断抑郁症研究进展[J].中国医学影像技术,2024,40(3):455~458 |
| 基于MRI影像组学和机器学习诊断抑郁症研究进展 |
| Research progresses of radiomics and machine learning based on MRI for diagnosing depressive disorder |
| 投稿时间：2023-09-05 修订日期：2023-12-29 |
| DOI：10.13929/j.issn.1003-3289.2024.03.028 |
| 中文关键词: 抑郁症 磁共振成像 机器学习 影像组学 |
| 英文关键词:depressive disorder magnetic resonance imaging machine learning radiomics |
| 基金项目:上海市浦东新区卫生系统重点学科(PWZxk2022-12)。 |
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| 中文摘要: |
| 抑郁症为常见神经心理疾病,目前尚无客观诊断标准。MRI可提供脑结构、白质纤维束完整性及静息态和任务态下脑功能等多方面信息;MRI影像组学和机器学习(ML)有助于建立个体化诊断抑郁症模型。本文对基于MRI影像组学及ML诊断抑郁症研究进展进行综述。 |
| 英文摘要: |
| Depressive disorder is a common neuropsychological disease, but the objective diagnostic criteria mains lack up till now. MRI can provide plenty information of brain structures, white matter fiber bundles as well as resting-state or task-related brain functions, etc. Radiomics and machine learning (ML) based on MRI can help to establish personalized diagnosis models of depression disorder. The research progresses of radiomics and ML based on MRI for diagnosing depressive disorder were reviewed in this article. |
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