Department of Radiology, Taichung Veterans General Hospital, Taichung, Taiwan.
Comput Med Imaging Graph. 2012 Jan;36(1):25-37. doi: 10.1016/j.compmedimag.2011.03.003. Epub 2011 Apr 14.
Variation of left ventricular myocardial volumes correlates closely with ischemic heart diseases. In clinical practice, because physicians and radiologists rely much on myocardial contour to diagnose many different cardiac diseases, automatic segmentation of left ventricular myocardium and quantifying myocardium characteristics is clinically beneficial. This paper presents a hybrid segmentation method for left ventricular myocardium on arterial phase of multi-detector row computed tomography (MDCT) imaging.
The proposed method utilizes an intensity transformation equation as a preprocessing procedure to enhance contrast and reduce noise in MDCT imaging. By setting the centroid of left ventricle (LV) as an initial seed, the conventional region growing method is employed to identify the endocardial contour of LV cavity for each slice. Then the level-set method (LSM) utilizes the extracted endocardial contour as initial contour to delineate the epicardium of LV. The two extracted contours are integrated to form the region of interest (ROI) of the LV. Finally, the ROIs from all slices are combined to obtain the volume of the whole LV myocardium.
Twenty-two healthy patients who had no symptoms of ischemic heart disease are applied to evaluate the performance of the proposed method. Compared with manual contours delineated by two experienced experts, the contouring results from computer simulation reveal that the proposed method always identifies similar contours as that obtained by the manual sketching.
The proposed method provides a robust and fast automatic contouring for LV myocardium on arterial phase of MDCT. The potential role of this technique may save much of the time required to manually sketch a precise contour with high stability.
左心室心肌容积的变化与缺血性心脏病密切相关。在临床实践中，由于医生和放射科医生主要依靠心肌轮廓来诊断许多不同的心脏疾病，因此自动分割左心室心肌并量化心肌特征在临床上是有益的。本文提出了一种基于多排螺旋 CT（MDCT）动脉期图像的左心室心肌混合分割方法。
所提出的方法利用强度变换方程作为预处理过程，以增强 MDCT 成像中的对比度并降低噪声。通过将左心室（LV）的质心设置为初始种子，采用传统的区域生长方法来识别每个切片的 LV 腔内心肌轮廓。然后，水平集方法（LSM）利用提取的心内膜轮廓作为初始轮廓来描绘 LV 的外膜。将这两个提取的轮廓整合形成 LV 的感兴趣区域（ROI）。最后，将所有切片的 ROI 组合起来得到整个 LV 心肌的体积。
对 22 名无缺血性心脏病症状的健康患者进行了应用评估。与由两位有经验的专家手动勾画的轮廓相比，计算机模拟的勾画结果表明，该方法始终能识别出与手动勾画相似的轮廓。
该方法为 MDCT 动脉期的左心室心肌提供了一种稳健、快速的自动轮廓勾画方法。该技术的潜在作用可能节省了手动精确勾画轮廓所需的大量时间，并且具有较高的稳定性。
