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首页> 外文期刊>Journal of Magnetics >Auto Segmentation Method for Electromagnetic Radiation Camera Myocardial Images
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Auto Segmentation Method for Electromagnetic Radiation Camera Myocardial Images

机译：电磁辐射相机心肌图像的自动分割方法

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摘要

Electromagnetic radiation camera (ERC) provides functional information about the left ventricle. We need new methods of quantitative analysis, such as the segmentation myocardial images for maximum utilization of ERC. The level set method(semi-automatic) based approach method that has excellent potential with regarding mapping topological change in 2D images but the crucial point is when stopping iteration to obtain the optimal segmentation result This study suggests the Courant-Friedrichs-Lewy (CFL) condition, feature measurement index (FMI), and modified Thompson Tau technique (MTTT) to investigate the optimal convergence problem. The CFL condition contributes to the stable numerical iteration of the level set, whereas the FMI and MTTT are used for exact iteration stopping. This study compared the auto segmentation method and the manual segmentation method through assessments. The results were so matched (82.39±13.92 %) so we can develop a 3D model that could be used to diagnose ischemic heart disease and infarction. The proposed segmentation method can help to diagnose the disease conveniently and accurately in the clinic.
机译：电磁辐射相机(ERC)提供左心室功能的信息。我们需要定量分析的新方法,如心肌图像分割伦理委员会的最大利用率。基于方法(半自动)方法很有可能与关于映射但关键拓扑变化的2 d图像点是获得时停止迭代这个研究表明最优分割结果the Courant-Friedrichs-Lewy (CFL)条件,特性测量指数(FMI)和修改汤普森τ技术(MTTT)调查最优收敛问题。有助于稳定的数值迭代水平集,而FMI和MTTT使用为精确迭代停止。自动分割方法和手册通过评估分割方法。结果匹配(82.39±13.92%)所以我们可以开发一个3 d模型,可以用来诊断缺血性心脏病和梗塞。提出的分割方法可以帮助诊断方便和准确诊所。

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