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Local Region with Optimized Boundary Driven Level Set Based Segmentation of Myocardial Ischemic Cardiac MR Images

机译:具有基于优化边界驱动级别的本地区域基于心肌缺血性心肌MR图像的分割

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In this work, an attempt is made to segment endocardium and epicardium of left ventricle in normal and myocardial ischemic cardiac magnetic resonance (CMR) images using local region with optimized boundary driven level set. Myocardial ischemia (MI) is a cardiac disorder that results in deprivation of oxygen supply to myocardium and can be analyzed by study of abnormal anatomical changes in CMR. This study is carried out on short-axis view CMR images from Medical Image Computing and Computer-Assisted Intervention (MICCAI) database. The edges are computed by simple Laplacian and Laplacian of Gaussian (LOG) operator. LOG is optimized to obtain enhanced edges of endocardium and epicardium. The quality of edge is validated with edge preservation index (EPI) and gradient magnitude similarity deviation (GMSD) measure. Local region with optimized boundary (LROB) driven level set is utilized for simultaneous segmentation of endocardium and epicardium of left ventricle in CMR images. The results are compared with local region (LR) driven and LR with LOG-driven level set. Further, the efficacy of the segmentation is validated with different similarity measures. The optimized LOG image visually shows better endocardium and epicardium contours. Optimized LOG with a higher EPI and lower GMSD provides better enhanced edges compared to Laplacian and LOG functions. The computed similarity measures for LR with LOG-driven level set are significantly higher compared to LR-based level set for segmentation of endocardium and epicardium. Further, LROB-driven level set shows higher similarity measures than LR with LOG-driven level set. Thus, LROB-driven level set provides better segmentation accuracy for epicardium and endocardium of left ventricle than LR-based level set and LR with LOG-driven level set. The efficiently segmented endocardium and epicardium could aid the diagnosis of myocardial ischemia with their ability to quantify anatomical changes in LV.
机译:在这项工作中,使用具有优化边界驱动水平集的局部区域对正常和心肌缺血性心脏磁共振(CMR)图像中左心室的左心室的细胞内膜和外膜进行试图。心肌缺血(MI)是一种心脏病,导致剥夺对心肌的氧气供应,可以通过研究CMR的异常解剖变性来分析。本研究在医学图像计算和计算机辅助干预(MICCAI)数据库中的短轴视图CMR图像上进行。边缘由简单的Laussian和Gaussian(Log)操作员的Laplacian计算。日志经过优化,以获得内膜内腔和外膜的增强边缘。使用边缘保存指数(EPI)和梯度幅度相似度偏差(GMSD)测量验证了边缘的质量。具有优化边界的局部区域(LROB)驱动水平集合用于在CMR图像中同时分割左心室的心内膜和心肌。将结果与局部区域(LR)驱动和LR进行比较,具有日志驱动的水平集。此外,通过不同的相似性测量验证了分割的功效。优化的日志图像视觉上显示出更好的内切管和心外膜轮廓。与Laplacian和Log功能相比,具有更高EPI和较低GMSD的优化日志提供更好的增强边缘。与基于LR的水平集合,LOG驱动级别集的LR的计算相似度措施显着更高,用于对心内膜和表皮的分段进行分段。此外,LROB驱动的水平集显示比LOG驱动级别集的更高的相似度量比LR更高。因此,LROB驱动的水平集为左心室的表皮和内膜内膜的细分精度比基于LR为基于LR的水平集和LOG驱动级别集的LR提供更好的分割精度。有效分段的内切心和外膜可以帮助诊断心肌缺血,其能够量化LV的解剖变化。

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