Local Birefringence Imaging by Similar Mueller Matrix Averaging Method in Catheter-Based Polarization-Sensitive Optical Coherence Tomography

Abstract

Local birefringence imaging provides the most intuitive polarization property of tissue, such as vascular plaque, in catheter-based polarization-sensitive optical coherence tomography (PS-OCT) imaging. We present a Local Birefringence Similar Mueller Matrix Averaging (LMMA) for catheter-based PS-OCT imaging. LMMA combines differential Mueller analysis, matrix decomposition, and noise compensation to address depolarization coupling and noise interference. Monte Carlo simulations show LMMA achieves 4.8% error under high noise and 4.4% under high depolarization─up to 84% improvement over the Stokes vector spectral binning (SSB) method. Polycarbonate imaging experiments yield 1.5% average error, 86% lower than the SSB. Ex-vivo porcine coronary artery imaging demonstrates significantly enhanced lipid and fibrous plaque phantom differentiation, with LMMA’s plaque recognition rate reaching 2.62 times that of SSB evaluated by spatial response of Laplacian operator (SRLO). The results show LMMA’s potential in advanced vascular imaging, particularly for monitoring and diagnosis of coronary artery disease.