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QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data
Name
1703.02942.pdf
Description
Submitted version
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2.06 MB
Format
Adobe PDF
Checksum (MD5)
b1eca474e900d90d3f9b817129c7a3af
Author(s)
Schirrmacher, Franziska
Köhler, Thomas
Husvogt, Lennart
Fujimoto, James G.
Hornegger, Joachim
Maier, Andreas K.
Date Issued
2017
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.
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
10.1007/978-3-319-66185-8_10
