1. Automatic Detection of Coronary Metallic Stent Struts Based on YOLOv3 and R-FCN

    Automatic Detection of Coronary Metallic Stent Struts Based on YOLOv3 and R-FCN

    An artificial stent implantation is one of the most effective ways to treat coronary artery diseases. It is vital in vascular medical imaging, such as intravascular optical coherence tomography (IVOCT), to be able to track the position of stents in blood vessels effectively. We trained two models, the “You Only Look Once” version 3 (YOLOv3) and the Region-based Fully Convolutional Network (R-FCN), to detect metal support struts in IVOCT, respectively. After rotating the original images in the training set for data augmentation, and modifying the scale of the conventional anchor box in both two algorithms to fit the size of ...

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