A fast seed detection using local geometrical feature for automatic tracking of coronary arteries in CTA
The seed points are detected for automatic coronary artery tracking from CCTA. The computational efficiency is improved using prior knowledge of vessel structure. Using proposed method, a particle filtering-based tracking algorithm is tested. ROC curve analysis shows the advantage of the proposed method.
seed detection roc curve coronary computed tomographic angiography (ccta) coronary artery segmentation centerline tracking