卷积神经网络以使用脑血管反应来评估静脉闭塞性疾病
Yashesh Dasari1, James Duffin2,3, Ece Su Sayin2,3
1Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
Healthcare (Basel, Switzerland)
|August 26, 2023
概括
一个新的卷积神经网络 (CNN) 系统通过分析脑血管反应 (CVR) 地图,有效地选狭闭塞性疾病 (SOD). 这种人工智能工具有助于早期诊断SOD,这是缺血性中风的主要原因.
科学领域:
- 神经成像是一种神经成像.
- 人工智能的人工智能
- 心血管医学 心血管医学
背景情况:
- 脑血管反应 (CVR) 对于使用BOLDMRI评估大脑血流变化至关重要.
- 静脉封闭性疾病 (SOD) 是缺血性中风的主要原因,需要改进的诊断工具.
- 目前的CVR分析有助于识别脑输液不足.
研究的目的:
- 开发基于卷积神经网络 (CNN) 的临床决策支持系统,用于SOD患者查.
- 区分健康和不健康的CVR地图,用于早期发现SOD.
- 加强脑血管疾病的早期诊断和临床管理.
主要方法:
- 在231张CVR图 (68名健康患者,163名SOD患者) 的数据集上开发和训练了一种CNN模型.
- 转移学习实验使用定制的预训练网络进行.
- 图像增强技术应用于培训和验证数据集.
主要成果:
- 采用双堆叠卷积层架构的定制CNN实现了最佳性能.
- 开发的系统展示了与专家临床解释一致的结果.
- 美国有线电视新闻网有效地区分了健康和SOD CVR地图.
结论:
- 基于CNN的CVR地图分析为自动SOD查提供了一个有前途的方法.
- 这种人工智能工具可以支持临床医生早期诊断脑血管功能不充分.
- 该研究强调了人工智能在改善对中风风险因素的管理方面的潜力.
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