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We present an automatic lumen segmentation method using uniqueness of connected region for intravascular optical coherence tomography (IVOCT), which can effectively remove the effect on lumen segmentation caused by blood artifacts. Utilizing the uniqueness of vascular wall on A-lines, we detect the A-lines shared by multiple connected regions, identify connected regions generated by blood artifacts using traversal comparison of connected regions' location, shared ratio and area ratio and then remove all artifacts. We compare these three methods by 216 challenging images with severe blood artifacts selected from clinical 1076 IVOCT images. The metrics of the proposed method are evaluated including Dice index, Jaccard index and accuracy of 94.57%, 90.12%, 98.02%. Compared with automatic lumen segmentation based on the previous morphological feature method and widely used dynamic programming method, the metrics of the proposed method are significantly enhanced, especially in challenging images with severe blood artifacts.

Catheter based polarization sensitive optical coherence tomography (PS-OCT) can provide composition information of coronary atherosclerotic plaque beyond the intensity based OCT, but it encounters a notable challenge that is how to reduce polarization properties variations owing to a rapidly rotating optical fiber in the catheter. Similar Jones matrix (SJM) and similar Mueller matrix (SMM) based polarization determination methods can provide a stable phase retardation imaging in a catheter based PS-OCT. In this paper, we systematically contrast SJM and SMM methods. Firstly, we theoretically illustrate the discrepancy between the eigenvalue decomposition in SJM and the polar decomposition in SMM. We find the SMM can reduce phase retardation error caused by non-coaxial diattenuation using polar decomposition. Secondly, we present a real incoherent averaging method in SMM. We find that incoherent averaging in SMM avoids a time-consuming global phase collection and more effectively reduce noise compared with complex coherent averaging in SJM. By polarization imaging for multiple biological tissues using a catheter based PS-OCT, we experimentally manifest that the areas with high diattenuation are highly correlated to the difference between images processed by SJM and SMM. At the same time, the SMM with incoherent averaging has a better performance than the SJM with coherent averaging especially at areas with low signal to noise ratio (SNR).

We present a three-dimensional (3D) spatial reconstruction of coronary arteries based on fusion of intravascular optical coherence tomography (IVOCT) and digital subtraction angiography (DSA). Centerline of vessel in DSA images is exacted by multi-scale filtering, adaptive segmentation, morphology thinning and Dijkstra's shortest path algorithm. We apply the cross-correction between lumen shapes of IVOCT and DSA images and match their stenosis positions to realize co-registration. By matching the location and tangent direction of the vessel centerline of DSA images and segmented lumen coordinates of IVOCT along pullback path, 3D spatial models of vessel lumen are reconstructed. Using 1121 distinct positions selected from eight vessels, the correlation coefficient between 3D IVOCT model and DSA image in measuring lumen radius is 0.94% and 97.7% of the positions fall within the limit of agreement by Bland-Altman analysis, which means that the 3D spatial reconstruction IVOCT models and DSA images have high matching level.