Motion Artifact Correction for OCT Microvascular Images Based on Image Feature Matching

Abstract

Optical coherence tomography angiography (OCTA), a functional extension of optical coherence tomography (OCT), is widely employed for high-resolution imaging of microvascular networks. However, due to the relatively low scan rate of OCT, the artifacts caused by the involuntary bulk motion of tissues severely impact the visualization of microvascular networks. This study proposes a fast motion correction method based on image feature matching for OCT microvascular images. First, the rigid motion-related mismatch between B-scans is compensated through the image feature matching based on the improved oriented FAST and rotated BRIEF algorithm. Then, the axial motion within A-scan lines in each B-scan image is corrected according to the displacement deviation between the detected boundaries achieved by the Scharr operator in a non-rigid transformation manner. Finally, an optimized intensity-based Doppler variance algorithm is developed to enhance the robustness of the OCTA imaging. The experimental results demonstrate the effectiveness of the method.