根据MRI,深度学习可以自动区分心肌炎患者与正常患者
Cosmin-Andrei Hatfaludi1,2, Aurelian Roșca3,4, Andreea Bianca Popescu5,6
1Advanta, Siemens SRL, 15 Noiembrie Bvd, Brasov, 500097, Romania. cosmin.hatfaludi@unitbv.ro.
The international journal of cardiovascular imaging
|November 7, 2024
概括
深度学习使用心血管磁共振成像 (CMRI) 准确检测心肌炎. 最好的结果来自于晚期加多增强 (LGE) 两室视图,用于诊断这种心脏炎症.
科学领域:
- 心脏病学 心脏病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 心肌炎是心肌组织的炎症,带来心力衰竭和心律失常的风险.
- 心血管磁共振成像 (CMRI) 对于诊断心脏疾病至关重要.
- 准确的CMRI解释对于及时治疗心肌炎至关重要.
研究的目的:
- 确定最佳的CMRI视图,以区分心肌炎与正常病例.
- 在CMRI中利用深度学习 (DL) 来自动检测心肌炎.
- 通过人工智能提高心血管成像诊断的准确性.
主要方法:
- 开发了一个深度学习框架,用于自动检测心肌炎.
- 分析包括来自269名参与者的单和多CMRI数据 (231名心肌炎,38名对照).
- 为了诊断性能,评估了各种CMRI视图和获取类型.
主要成果:
- 在检测心肌炎方面,DL模型实现了96.9%的加权准确度.
- 晚期加多增强 (LGE) 两室视图产生了最高的诊断准确度.
- 自动检测表明,在区分心肌炎和正常病例方面,有很大的潜力.
结论:
- 深度学习使用CMRI有效地区分心肌炎和正常病例.
- 特定的CMRI视图,特别是LGE2室视图,是基于DL的心肌炎检测的最佳选择.
- 这种由人工智能驱动的方法显示出改善心肌炎诊断和患者治疗结果的前景.
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