QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data
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1703.02942.pdf
Description
Submitted version
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2.06 MB
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Author(s)
Schirrmacher, Franziska
Köhler, Thomas
Husvogt, Lennart
Fujimoto, James G.
Hornegger, Joachim
Maier, Andreas K.
Date Issued
September 2017
Journal
Lecture Notes in Computer Science
Publisher
Springer International Publishing
Citation
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."
Version
Original manuscript
Abstract
© 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.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Research Laboratory of Electronics
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DOI of Published Version
https://doi.org/10.1007/978-3-319-66185-8_10
