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

Area of Science:

• Ophthalmology
• Biomedical Imaging
• Medical Technology

Background:

• Optical coherence tomography angiography (OCTA) provides high-resolution imaging of microvascular networks.
• Involuntary tissue motion during OCTA scans introduces artifacts, hindering microvascular visualization.
• Existing methods struggle with the low scan rate of OCT, leading to motion-induced image degradation.

Purpose of the Study:

• To develop and validate a fast motion correction method for OCTA microvascular imaging.
• To mitigate artifacts caused by involuntary tissue motion in OCTA scans.
• To enhance the robustness and visualization quality of OCTA imaging.

Main Methods:

• Implemented a fast motion correction approach utilizing image feature matching for OCT microvascular images.
• Compensated for rigid motion between B-scans using improved oriented FAST and rotated BRIEF algorithm-based feature matching.
• Corrected axial motion within A-scan lines via non-rigid transformation based on Scharr operator-detected boundary displacements.
• Developed an optimized intensity-based Doppler variance algorithm to improve OCTA imaging robustness.

Main Results:

• The proposed method effectively corrects rigid and non-rigid motion artifacts in OCTA scans.
• Enhanced visualization of microvascular networks was achieved by reducing motion-induced distortions.
• Experimental results confirmed the effectiveness of the developed fast motion correction technique.
• The optimized Doppler variance algorithm improved the overall quality and reliability of OCTA imaging.

Conclusions:

• The proposed fast motion correction method significantly improves OCTA imaging of microvascular networks.
• This technique addresses the critical challenge of motion artifacts in OCTA, enabling clearer visualization.
• The study demonstrates a robust approach for enhancing OCTA image quality in the presence of tissue motion.