QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data

Schirrmacher F, Köhler T, Husvogt L, Fujimoto JG, Hornegger J, Maier A (2017)

Publication Type: Conference contribution, Conference Contribution

Publication year: 2017

Publisher: Springer Verlag

Edited Volumes: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Book Volume: 10434 LNCS

Pages Range: 83-91

Conference Proceedings Title: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2017, Proceedings, Part II

Event location: Quebec City, QC, Canada

ISBN: 9783319661841

URI: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2017/Schirrmacher17-QQS.pdf

DOI: 10.1007/978-3-319-66185-8_10

Abstract

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.

Authors with CRIS profile

Involved external institutions

Massachusetts Institute of Technology (MIT) United States (USA) (US)

How to cite

APA:

Schirrmacher, F., Köhler, T., Husvogt, L., Fujimoto, J.G., Hornegger, J., & Maier, A. (2017). QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data. In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2017, Proceedings, Part II (pp. 83-91). Quebec City, QC, Canada: Springer Verlag.

MLA:

Schirrmacher, Franziska, et al. "QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data." Proceedings of the Medical Image Computing and Computer-Assisted Intervention, Quebec City, QC, Canada Springer Verlag, 2017. 83-91.

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