Abstract
Cardiovascular disease has seriously affected the lives of modern people. One of the most commonly used imaging methods for diagnosing cardiovascular disease is computed tomography angiography (CTA). To generate a diagnosis report for doctors, every coronary artery needs to be identified and segmented, including the right coronary artery (RCA), the posterior descending artery (PDA), the posterior lateral branch (PLB), the left circumflex (LCx), the left anterior descending branch (LAD), the ramus intermedius (RI), the obtuse marginal branches (OM1, OM2), and the diagonal branches (D1, D2). In this paper, we proposed a coronary artery automatic identification algorithm, which performs better in terms of accuracy than other similar algorithms and works efficiently. Normally, each Coronary Computed Tomographic Angiography (CCTA) dataset can be completed within seconds. This algorithm fully complies with the coronary label standard established by the Society of Cardiovascular Computed Tomography (SCCT). This algorithm has been put into operation in more than 100 hospitals for over one year. According to all previous tests, the labels obtained from the algorithm were compared with results manually corrected by several experts. Among 892 CCTA datasets, 95.96% of the labels obtained from the algorithms were correct.
Highlights
Coronary computed tomographic angiography (CCTA) is a non-invasive imaging modality that can visualize the heart as well as the coronary arteries and has become the main method for diagnosing coronary artery disease [1], [2]
The left coronary artery is on the positive side of the x-axis, while the right coronary artery is on the negative side of the x-axis
IDENTIFICATION OF THE right coronary artery (RCA), R-posterior descending artery (PDA) AND R-posterior lateral branch (PLB) FROM THE RIGHT CORONARY ARTERY In Fig. 3, we are mainly concerned with three blood arteries, i.e., RCA, Right Posterior Descending Artery (R-PDA) and Right Posterior Lateral Branch (R-PLB), in the right coronary section
Summary
Coronary computed tomographic angiography (CCTA) is a non-invasive imaging modality that can visualize the heart as well as the coronary arteries and has become the main method for diagnosing coronary artery disease [1], [2]. To generate the automatic diagnostic report efficiently and accurately, the identification of coronary arteries should be in strict accordance with the CCTA standards [14], [15]. Zhang et al.: Automatic Identification of Coronary Arteries in CCTA including the RCA, LM, LCx and LAD, and based on the first step, the method identifies all the side branches. The net uses the spatial locations and directions of arteries as features and performs an evaluation by a tenfold cross-validation All these methods enjoy a relatively high accuracy. High accuracy is achieved on the side branches This method enjoys a higher efficiency, normally processing each CCTA dataset within seconds. This work does not try to identify L-PLB and L-PDA because most diagnosis processes do not consider these two arteries [13], [14]
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