QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data
Author(s)Schirrmacher, Franziska; Köhler, Thomas; Husvogt, Lennart; Fujimoto, James G.; Hornegger, Joachim; Maier, Andreas K.; ... Show more Show less
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© Springer International Publishing AG 2017. Optical coherence tomography (OCT) enables high-resolution and non-invasive 3D imaging of the human retina but is inherently impaired by speckle noise. This paper introduces a spatio-temporal denoising algorithm for OCT data on a B-scan level using a novel quantile sparse image (QuaSI) prior. To remove speckle noise while preserving image structures of diagnostic relevance, we implement our QuaSI prior via median filter regularization coupled with a Huber data fidelity model in a variational approach. For efficient energy minimization, we develop an alternating direction method of multipliers (ADMM) scheme using a linearization of median filtering. Our spatio-temporal method can handle both, denoising of single B-scans and temporally consecutive B-scans, to gain volumetric OCT data with enhanced signal-to-noise ratio. Our algorithm based on 4 B-scans only achieved comparable performance to averaging 13 B-scans and outperformed other current denoising methods.
Lecture Notes in Computer Science
Springer International Publishing
Schirrmacher, Franziska, Köhler, Thomas, Husvogt, Lennart, Fujimoto, James G., Hornegger, Joachim et al. 2017. "QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data."