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

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(Konferenzbeitrag)


Details zur Publikation

Autor(en): Schirrmacher F, Köhler GT, Husvogt L, Fujimoto JG, Hornegger J, Maier A
Titel Sammelwerk: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Verlag: Springer Verlag
Jahr der Veröffentlichung: 2017
Band: 10434 LNCS
Tagungsband: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2017, Proceedings, Part II
Seitenbereich: 83-91
ISBN: 9783319661841
ISSN: 1611-3349


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.


FAU-Autoren / FAU-Herausgeber

Hornegger, Joachim Prof. Dr.-Ing.
Lehrstuhl für Informatik 5 (Mustererkennung)
Husvogt, Lennart
Lehrstuhl für Informatik 5 (Mustererkennung)
Köhler, Thomas
Lehrstuhl für Informatik 5 (Mustererkennung)
Maier, Andreas Prof. Dr.-Ing.
Lehrstuhl für Informatik 5 (Mustererkennung)
Schirrmacher, Franziska
Lehrstuhl für Informatik 5 (Mustererkennung)


Autor(en) der externen Einrichtung(en)
Massachusetts Institute of Technology (MIT)


Zitierweisen

APA:
Schirrmacher, F., Köhler, G.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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Zuletzt aktualisiert 2018-19-12 um 11:38