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首页> 外文会议>Conference on Medical Imaging: Computer-Aided Diagnosis >Automated segmentation and tracking of coronary arteries in ECG-gated cardiac CT scans
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Automated segmentation and tracking of coronary arteries in ECG-gated cardiac CT scans

机译：ECG门控心脏CT扫描中的自动分割和跟踪冠状动脉

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Cardiac CT has been reported to be an effective means for clinical diagnosis of coronary artery plaque disease. We are investigating the feasibility of developing a computer-assisted image analysis (CAA) system to assist radiologist in detection of coronary artery plaque disease in ECG-gated cardiac CT scans. The heart region was first extracted using morphological operations and an adaptive EM thresholding method. Vascular structures in the heart volume were enhanced by 3D multi-scale filtering and analysis of the eigenvalues of Hessian matrices using a vessel enhancement response function specially designed for coronary arteries. The enhanced vascular structures were then segmented by an EM estimation method. Finally, our newly developed 3D rolling balloon vessel tracking method (RBVT) was used to track the segmented coronary arteries. Starting at two manually identified points located at the origins of left and right coronary artery (LCA and RCA), the RBVT method moved a sphere of adaptive diameter along the vessels, tracking the vessels and identifying its branches automatically to generate the left and right coronary arterial trees. Ten cardiac CT scans that contained various degrees of coronary artery diseases were used as test data set for our vessel segmentation and tracking method. Two experienced thoracic radiologists visually examined the computer tracked coronary arteries on a graphical interface to count untracked false-negative (FN) branches (segments). A total of 27 artery segments were identified to be FNs in the 10 cases, ranging from 0 to 6 FN segments in each case. No FN artery segment was found in 2 cases.
机译：据报道，心脏CT是冠状动脉斑斑临床诊断的有效手段。我们正在研究开发计算机辅助图像分析（CAA）系统的可行性，以帮助放射科医生检测心电图心脏CT扫描中的冠状动脉斑斑。首先利用形态操作和自适应EM阈值方法提取心脏区域。通过专门为冠状动脉专为冠状动脉设计的血管增强响应函数来增强心脏体积中的血管结构。然后通过EM估计方法进行增强的血管结构。最后，我们新开发的3D滚动气囊血管跟踪方法（RBVT）用于跟踪分段冠状动脉。从位于左右冠状动脉（LCA和RCA）的两个手动鉴定的点开始，RBVT方法移动沿着血管的自适应直径的球体，跟踪血管并自动识别其分支以产生左右冠状动脉动脉树。含有各种冠状动脉疾病的十个心脏CT扫描用作我们的血管分割和跟踪方法的测试数据集。两位经验丰富的胸部放射科医师在视觉上检查了图形界面上的计算机跟踪的冠状动脉，以计算未触发的假阴性（Fn）分支（段）。在10例中，共识别出27个动脉段，在每种情况下为0到6个FN段。在2例中没有发现FN动脉细分。

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