Dakua Sarada Prasad, Sahambi J S
Department of Electronics and Communication Engineering, Indian Institute of Technology, Guwahati, India.
Cardiovasc Eng. 2010 Sep;10(3):163-8. doi: 10.1007/s10558-010-9102-3.
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.
从心脏磁共振（CMR）图像中对心脏功能进行定量评估需要识别心肌壁。这通常需要临床医生查看图像并交互式地描绘轮廓。特别是，在从患有严重疾病的受试者获得的CMR图像中，检测左心室的心肌壁是一项艰巨的任务。本文提出了一种自动勾勒左心室轮廓的方法。为了分割左心室，本文建议结合两种方法。高斯加权函数差异（DoG）被新引入到随机游走方法中以提取血池（内部轮廓）。心肌壁（外部轮廓）通过一种改进的主动轮廓方法分割出来，该方法以血池边界作为初始轮廓。在CMR图像中获得的有前景的实验结果证明了我们方法的潜力。
