Automated coronary artery tree extraction in coronary CT angiography using a multiscale enhancement and dynamic balloon tracking (MSCAR-DBT) method.
Automated coronary artery tree extraction in coronary CT angiography using a multiscale enhancement and dynamic balloon tracking (MSCAR-DBT) method.
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DOI：
10.1016/j.compmedimag.2011.04.001
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发表时间：
2012-01
影响因子：
5.7
通讯作者：
Kazerooni, Ella A.
中科院分区：
文献类型：
--
作者：
Zhou, Chuan;Chan, Heang-Ping;Chughtai, Aamer;Patel, Smita;Hadjiiski, Lubomir M.;Wei, Jun;Kazerooni, Ella A.
评价我们用于分割和跟踪冠状动脉树的原型方法，这是开发计算机辅助检测（CADe）系统的基础，以帮助放射科医生在冠状动脉CT血管造影（cCTA）扫描中检测非钙化斑块。首先通过形态学操作和基于期望最大化（EM）估计的自适应阈值方法提取心脏区域。使用多尺度冠状动脉响应（MSCAR）方法增强和分割心脏区域内的血管结构，该方法结合了3D多尺度滤波、Hessian矩阵特征值分析和EM估计分割。在血管结构分割后，冠状动脉的三维动态气球跟踪（DBT）方法进行跟踪。DBT方法从位于左和右冠状动脉（LCA和RCA）起点的两个手动识别的种子点开始，用于提取动脉树。采用MSCAR-DBT方法和GE Advantage工作站对20例ECG门控造影增强cCTA扫描的数据集进行冠状动脉树提取。两名经验丰富的胸部放射科医生目视检查了原始cCTA扫描上的冠状动脉和分段血管的渲染体积，以计算两种方法的未跟踪假阴性（FN）节段和假阳性（FP）。对于20例病例中可见的冠状动脉节段，放射科医师发现我们的MSCAR-DBT方法遗漏了25个节段，个别病例中的FN节段范围为0至5个，GE软件遗漏了55个动脉节段，个别病例中的FN节段范围为0至7个。在我们和GE冠状动脉树中分别识别出19和15个FP，在个体病例中两种方法的FP范围分别为0至4个。初步研究表明，我们的MSCAR-DBT方法分割和跟踪冠状动脉树的可行性。结果表明，我们的方法和GE软件都可以很好地提取冠状动脉树，我们的方法的性能优于GE软件在这个小数据集的上级。进一步的研究正在进行中，以开发用于改进分割和跟踪精度的方法。
To evaluate our prototype method for segmentation and tracking of the coronary arterial tree, which is the foundation for a computer-aided detection (CADe) system to be developed to assist radiologists in detecting non-calcified plaques in coronary CT angiography (cCTA) scans. The heart region was first extracted by a morphological operation and an adaptive thresholding method based on expectation-maximization (EM) estimation. The vascular structures within the heart region were enhanced and segmented using a multiscale coronary response (MSCAR) method that combined 3D multiscale filtering, analysis of the eigen values of Hessian matrices and EM estimation segmentation. After the segmentation of vascular structures, the coronary arteries were tracked by a 3D dynamic balloon tracking (DBT) method. The DBT method started at two manually identified seed points located at the origins of the left and right coronary arteries (LCA and RCA) for extraction of the arterial trees. The coronary arterial trees of a data set containing 20 ECG-gated contrast-enhanced cCTA scans were extracted by our MSCAR-DBT method and a clinical GE Advantage workstation. Two experienced thoracic radiologists visually examined the coronary arteries on the original cCTA scans and the rendered volume of segmented vessels to count the untracked false-negative (FN) segments and false positives (FPs) for both methods. For the visible coronary arterial segments in the 20 cases, the radiologists identified that 25 segments were missed by our MSCAR-DBT method, ranging from 0 to 5 FN segments in individual cases, and that 55 artery segments were missed by the GE software, ranging from 0 to 7 FN segments in individual cases. 19 and 15 FPs were identified in our and the GE coronary trees, ranging from 0 to 4 FPs for both methods in individual cases, respectively. The preliminary study demonstrates the feasibility of our MSCAR-DBT method for segmentation and tracking coronary artery trees. The results indicated that both our method and GE software can extract coronary artery trees reasonably well and the performance of our method is superior to that of GE software in this small data set. Further studies are underway to develop methods for improvement of the segmentation and tracking accuracy.
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影响因子：
3.8
作者：
Zhou, Chuan;Chan, Heang-Ping;Kazerooni, Ella A.
通讯作者：
Kazerooni, Ella A.
影响因子：
10.6
作者：
Kutka, R;Stier, S
通讯作者：
Stier, S
影响因子：
2.8
作者：
Fine, JJ;Hopkins, CB;Newton, FC
通讯作者：
Newton, FC
影响因子：
120.7
作者：
Garcia, Mario J.;Lessick, Jonathan;Hoffmann, Martin H. K.
通讯作者：
Hoffmann, Martin H. K.
影响因子：
19.7
作者：
Rubin, GD;Paik, DS;Napel, S
通讯作者：
Napel, S