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Variational level set method with shape constraint and application to oedema cardiac magnetic resonance image

机译:具有形状约束的变化水平集方法及其在水肿心脏磁共振图像中的应用

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Quantification of oedema area after acute myocardial infarction (MI) is very important in clinical prognosis for differentiating the viable and death myocardial tissues. In order to quantify oedema region, the first step is to segment the myocardial wall accurately. This paper applies variational level set method with shape constraint to oedema cardiac magnetic resonance (CMR) images. Shape information of the myocardial wall is introduced into the variational level set formulation, and the performance of the automatic method is tested on T2 weighted CMR images from 8 patients, and compared with manual analysis from two clinical experts. Results show that the proposed automatic segmentation framework can segment left ventricle (LV) boundary with no significant difference compared to manual segmentation,
机译:急性心肌梗死(MI)后水肿区域的量化对于区分存活和死亡心肌组织在临床预后中非常重要。为了量化水肿区域,第一步是准确地分割心肌壁。本文将具有形状约束的变化水平集方法应用于水肿心脏磁共振(CMR)图像。将心肌壁的形状信息引入变化水平集公式,并在8位患者的T2加权CMR图像上测试自动方法的性能,并与两名临床专家的手动分析进行比较。结果表明,提出的自动分割框架可以分割左心室(LV)边界,与手动分割相比没有显着差异,

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