Decoupling structural artifacts in fiber optic imaging by applying compressive sensing

Jae Ho Han; Sang Min Yoon; Gang Joon Yoon

doi:10.1016/j.ijleo.2015.05.045

Decoupling structural artifacts in fiber optic imaging by applying compressive sensing

Jae Ho Han, Sang Min Yoon, Gang Joon Yoon

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

Endoscopic optical coherence tomography (OCT) is an emerging method for noninvasive microscopic probing in biomedicine. In this paper, the feasibility of alleviating the pixelated structural artifacts created by a fiber bundle-based OCT imaging method is investigated using a novel statistical analysis. We demonstrate an efficient nonparametric iterative compressive sensing (CS) technique that is efficient in reconstructing the original pattern shape from a pixelated image of a reference US Air Force resolution chart. An efficient implementation scheme for the shape recovery is presented along with the results of experiments that demonstrate a peak signal-to-noise ratio of 18 dB and a noise variation of less than 0.3 dB with no honeycomb effect in the image is obtained after 40 iterations which is significantly efficient than the previous iterative method of learning image priors.

Original language	English
Pages (from-to)	2013-2017
Number of pages	5
Journal	Optik
Volume	126
Issue number	19
DOIs	https://doi.org/10.1016/j.ijleo.2015.05.045
Publication status	Published - 2015 Oct 1

Keywords

Biomedical imaging
Compressive sensing
Image reconstruction
Microscopy
Optical coherence tomography

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Electrical and Electronic Engineering

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10.1016/j.ijleo.2015.05.045

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title = "Decoupling structural artifacts in fiber optic imaging by applying compressive sensing",

abstract = "Endoscopic optical coherence tomography (OCT) is an emerging method for noninvasive microscopic probing in biomedicine. In this paper, the feasibility of alleviating the pixelated structural artifacts created by a fiber bundle-based OCT imaging method is investigated using a novel statistical analysis. We demonstrate an efficient nonparametric iterative compressive sensing (CS) technique that is efficient in reconstructing the original pattern shape from a pixelated image of a reference US Air Force resolution chart. An efficient implementation scheme for the shape recovery is presented along with the results of experiments that demonstrate a peak signal-to-noise ratio of 18 dB and a noise variation of less than 0.3 dB with no honeycomb effect in the image is obtained after 40 iterations which is significantly efficient than the previous iterative method of learning image priors.",

keywords = "Biomedical imaging, Compressive sensing, Image reconstruction, Microscopy, Optical coherence tomography",

author = "Han, {Jae Ho} and Yoon, {Sang Min} and Yoon, {Gang Joon}",

note = "Funding Information: J. H. Han was supported in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF-2013R1A1A2062448) and partly supported by the ICT R&D program of MSIP/IITP [B0101-15-0307, Basic Software Research in Human-level Lifelong Machine Learning (Machine Learning Center)]. S. M. Yoon was supported by the ICT program of MSIP/IITP, Republic of Korea (#B0101-15-1347) and also supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2014R1A1A1002890). G.-J. Yoon was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2009-0093827). J.-H. Han and S. M. Yoon contributed equally in this work. Publisher Copyright: {\textcopyright} 2015 Elsevier GmbH. All rights reserved.",

year = "2015",

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doi = "10.1016/j.ijleo.2015.05.045",

language = "English",

volume = "126",

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AU - Han, Jae Ho

AU - Yoon, Sang Min

AU - Yoon, Gang Joon

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PY - 2015/10/1

Y1 - 2015/10/1

N2 - Endoscopic optical coherence tomography (OCT) is an emerging method for noninvasive microscopic probing in biomedicine. In this paper, the feasibility of alleviating the pixelated structural artifacts created by a fiber bundle-based OCT imaging method is investigated using a novel statistical analysis. We demonstrate an efficient nonparametric iterative compressive sensing (CS) technique that is efficient in reconstructing the original pattern shape from a pixelated image of a reference US Air Force resolution chart. An efficient implementation scheme for the shape recovery is presented along with the results of experiments that demonstrate a peak signal-to-noise ratio of 18 dB and a noise variation of less than 0.3 dB with no honeycomb effect in the image is obtained after 40 iterations which is significantly efficient than the previous iterative method of learning image priors.

AB - Endoscopic optical coherence tomography (OCT) is an emerging method for noninvasive microscopic probing in biomedicine. In this paper, the feasibility of alleviating the pixelated structural artifacts created by a fiber bundle-based OCT imaging method is investigated using a novel statistical analysis. We demonstrate an efficient nonparametric iterative compressive sensing (CS) technique that is efficient in reconstructing the original pattern shape from a pixelated image of a reference US Air Force resolution chart. An efficient implementation scheme for the shape recovery is presented along with the results of experiments that demonstrate a peak signal-to-noise ratio of 18 dB and a noise variation of less than 0.3 dB with no honeycomb effect in the image is obtained after 40 iterations which is significantly efficient than the previous iterative method of learning image priors.

KW - Biomedical imaging

KW - Compressive sensing

KW - Image reconstruction

KW - Microscopy

KW - Optical coherence tomography

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Decoupling structural artifacts in fiber optic imaging by applying compressive sensing

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