Automatic Identification Of Side Branch And Main Vascular Measurements In Intravascular Optical Coherence Tomography Images

Automatic identification of side branch and main vascular measurements in IVOCT images take critical roles in pre-interventional decision making for coronary artery disease treatment. Very little works have been presented on these tasks. In this paper, we proposed a novel side branch identification algorithm which utilizes a newly defined global curvature feature to identify the ostium of side branch. Based on identification results, the main vascular can be segmented automatically for measurements. In the measurement of main vascular, the diameter of maximum inscribed circle of main vascular is proposed for the first time, which could be helpful in stent size decision. The qualitative and quantitative validation results demonstrated that the proposed algorithm is effective and accurate.