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Optical coherence tomography angiography (OCTA) is a novel and clinicallypromising imaging modality to image retinal and sub-retinal vasculature. Basedon repeated optical coherence tomography (OCT) scans, intensity changes areobserved over time and used to compute OCTA image data. OCTA data are prone tonoise and artifacts caused by variations in flow speed and patient movement. Wepropose a novel iterative maximum a posteriori signal recovery algorithm inorder to generate OCTA volumes with reduced noise and increased image quality.This algorithm is based on previous work on probabilistic OCTA signal modelsand maximum likelihood estimates. Reconstruction results using total variationminimization and wavelet shrinkage for regularization were compared against anOCTA ground truth volume, merged from six co-registered single OCTA volumes.The results show a significant improvement in peak signal-to-noise ratio andstructural similarity. The presented algorithm brings together OCTA imagegeneration and Bayesian statistics and can be developed into new OCTA imagegeneration and denoising algorithms.

Maximum a posteriori signal recovery for optical coherence tomography angiography image generation and denoising