Motion artifact removal of optical coherence tomography angiography based on tensor voting

摘要

Optical coherence tomography angiography (OCTA) is a promising tool for imaging subsurface microvascular networksowing to its micron-level resolution and high sensitivity. However, it is not uncommon that OCTA imaging tend to sufferfrom strip artifacts induced by tissue motion. Although various algorithms for motion correction have been reported, amethod that enables motion correction on a single en face OCTA image remains a challenge. In this study, we proposed anovel motion correction approach based on microvasculature detection and broken gap filling. Unlike previous methodsusing registration to restore disturbed vasculature during motion artifact removal, tensor voting is performed in individualprojected image to connect the broken vasculature. Both simulation and in vivo 3D OCTA imaging of mouse bladder areperformed to validate the effectiveness of this method. A comparison of in vivo images before and after motion correctionshows that our method effectively corrects tissue motion artifacts while preserving continuity of vasculature network.Furthermore, in vivo results of this technique are presented to demonstrate the utility for imaging tumor angiogenesis inthe mouse bladder.