心脏MR左心室分割的策略方法。

Sarada Prasad Dakua, J S Sahambi
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引用次数: 3

摘要

从心脏磁共振(CMR)图像定量评估心脏功能需要识别心肌壁。这通常需要临床医生查看图像并交互式地跟踪轮廓。特别是,对于患有严重疾病的受试者,在CMR图像中检测左心室心肌壁是一项困难的任务。提出了一种自动绘制左心室轮廓的方法。为了分割左心室,本文提出了两种方法的结合。在血池(内轮廓)提取的随机游走方法中引入了高斯加权函数差分法(DoG)。采用一种以血池边界为初始轮廓的改进活动轮廓法分割心肌壁(外轮廓)。在CMR图像中有希望的实验结果证明了我们的方法的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A strategic approach for cardiac MR left ventricle segmentation.

Quantitative evaluation of cardiac function from cardiac magnetic resonance (CMR) images requires the identification of the myocardial walls. This generally requires the clinician to view the image and interactively trace the contours. Especially, detection of myocardial walls of left ventricle is a difficult task in CMR images that are obtained from subjects having serious diseases. An approach to automated outlining the left ventricular contour is proposed. In order to segment the left ventricle, in this paper, a combination of two approaches is suggested. Difference of Gaussian weighting function (DoG) is newly introduced in random walk approach for blood pool (inner contour) extraction. The myocardial wall (outer contour) is segmented out by a modified active contour method that takes blood pool boundary as the initial contour. Promising experimental results in CMR images demonstrate the potentials of our approach.

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