首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Ultrasound IMT measurement on a multi-ethnic and multi-institutional database: Our review and experience using four fully automated and one semi-automated methods
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Ultrasound IMT measurement on a multi-ethnic and multi-institutional database: Our review and experience using four fully automated and one semi-automated methods

机译:在多种族和多机构数据库中进行超声IMT测量:我们使用四种全自动和一种半自动化方法进行的回顾和经验

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Automated and high performance carotid intima-media thickness (IMT) measurement is gaining increasing importance in clinical practice to assess the cardiovascular risk of patients. In this paper, we compare four fully automated IMT measurement techniques (CALEX, CAMES, CARES and CAUDLES) and one semi-automated technique (FOAM). We present our experience using these algorithms, whose lumen-intima and media-adventitia border estimation use different methods that can be: (a) edge-based; (b) training-based; (c) feature-based; or (d) directional Edge-Flow based. Our database (DB) consisted of 665 images that represented a multi-ethnic group and was acquired using four OEM scanners. The performance evaluation protocol adopted error measures, reproducibility measures, and Figure of Merit (FoM). FOAM showed the best performance, with an IMT bias equal to 0.025 ± 0.225. mm, and a FoM equal to 96.6%. Among the four automated methods, CARES showed the best results with a bias of 0.032 ± 0.279. mm, and a FoM to 95.6%, which was statistically comparable to that of FOAM performance in terms of accuracy and reproducibility. This is the first time that completely automated and user-driven techniques have been compared on a multi-ethnic dataset, acquired using multiple original equipment manufacturer (OEM) machines with different gain settings, representing normal and pathologic cases.
机译:自动化和高性能颈动脉内中膜厚度(IMT)测量在临床实践中越来越重要,以评估患者的心血管风险。在本文中,我们比较了四种完全自动化的IMT测量技术(CALEX,CAMES,CARES和CAUDLES)和一种半自动化技术(FOAM)。我们介绍了使用这些算法的经验,这些算法的流明内膜边界和中膜外膜边界估计使用不同的方法,这些方法可以是:(a)基于边缘的; (b)以培训为基础; (c)基于特征;或(d)基于定向边缘流。我们的数据库(DB)由665个代表多族裔群体的图像组成,并使用四台OEM扫描仪进行了采集。性能评估协议采用了错误措施,可重复性措施和品质因数(FoM)。 FOAM表现最佳,IMT偏差等于0.025±0.225。毫米,FoM等于96.6%。在这四种自动化方法中,CARES表现出最好的结果,偏差为0.032±0.279。毫米,FoM达到95.6%,就准确性和可重复性而言,在统计学上与FOAM性能相当。这是首次在多族裔数据集上比较了完全自动化和用户驱动的技术,该数据集是使用具有不同增益设置(代表正常和病理情况)的多台原始设备制造商(OEM)机器获得的。

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