Dreconstruction of coronary artery containing stent strut based on OCT images

Optical coherence tomography (OCT) has become a new method for detecting coronary artery disease,which is widely used for its high resolution.In this article,we study algorisms for 3D images reconstructing from 2D cross-sectional coronary images.The images are firstly denoised by self-adapted median filter algorithm.According to the characteristics of OCT images,an improved Otsu algorithm is used to segment the coronary vessels.A new full automatic algorithm is then applied for stent detection.All 2D OCT images are converted into polar coordination.Based on the visible stent features shown in the OCT images,with global intensity histogram and intensity contours,we can identify candidate pixels and remove the artifacts to locate the stent on the lower boundary.By merging adjacent candidate pixels to a point on the stent,we can then accurately delineate the stent position.This process does not require a priori knowledge of stent status and the contours of blood vessels.It is immune from interferences induced by artifacts and avoids the accuracy problem of clustering algorithm.The final results show that the proposed method is able to conduct 3D reconstruction and fusion effectively