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Endoscopic image enhancement with noise suppression

Stereoscopic endoscopes have been used increasingly in minimally invasive surgery to visualise the organ surface and manipulate various surgical tools. However, insufficient and irregular light sources become major challenges for endoscopic surgery. Not only do these conditions hinder image processi...

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Detalles Bibliográficos
Autores principales: Xia, Wenyao, Chen, Elvis C.S., Peters, Terry
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Institution of Engineering and Technology 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6222180/
https://www.ncbi.nlm.nih.gov/pubmed/30464845
http://dx.doi.org/10.1049/htl.2018.5067
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author Xia, Wenyao
Chen, Elvis C.S.
Peters, Terry
author_facet Xia, Wenyao
Chen, Elvis C.S.
Peters, Terry
author_sort Xia, Wenyao
collection PubMed
description Stereoscopic endoscopes have been used increasingly in minimally invasive surgery to visualise the organ surface and manipulate various surgical tools. However, insufficient and irregular light sources become major challenges for endoscopic surgery. Not only do these conditions hinder image processing algorithms, sometimes surgical tools are barely visible when operating within low-light regions. In addition, low-light regions have low signal-to-noise ratio and metrication artefacts due to quantisation errors. As a result, present image enhancement methods usually suffer from heavy noise amplification in low-light regions. In this Letter, the authors propose an effective method for endoscopic image enhancement by identifying different illumination regions and designing the enhancement design criteria for desired image quality. Compared with existing image enhancement methods, the proposed method is able to enhance the low-light region while preventing noise amplification during image enhancement process. The proposed method is tested with 200 images acquired by endoscopic surgeries. Computed results show that the proposed algorithm can outperform state-of-the-art algorithms for image enhancement, in terms of naturalness image quality evaluator and illumination index.
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spelling pubmed-62221802018-11-21 Endoscopic image enhancement with noise suppression Xia, Wenyao Chen, Elvis C.S. Peters, Terry Healthc Technol Lett Special Issue: Papers from the 12th Workshop on Augmented Environments for Computer-Assisted Interventions Stereoscopic endoscopes have been used increasingly in minimally invasive surgery to visualise the organ surface and manipulate various surgical tools. However, insufficient and irregular light sources become major challenges for endoscopic surgery. Not only do these conditions hinder image processing algorithms, sometimes surgical tools are barely visible when operating within low-light regions. In addition, low-light regions have low signal-to-noise ratio and metrication artefacts due to quantisation errors. As a result, present image enhancement methods usually suffer from heavy noise amplification in low-light regions. In this Letter, the authors propose an effective method for endoscopic image enhancement by identifying different illumination regions and designing the enhancement design criteria for desired image quality. Compared with existing image enhancement methods, the proposed method is able to enhance the low-light region while preventing noise amplification during image enhancement process. The proposed method is tested with 200 images acquired by endoscopic surgeries. Computed results show that the proposed algorithm can outperform state-of-the-art algorithms for image enhancement, in terms of naturalness image quality evaluator and illumination index. The Institution of Engineering and Technology 2018-09-14 /pmc/articles/PMC6222180/ /pubmed/30464845 http://dx.doi.org/10.1049/htl.2018.5067 Text en http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/)
spellingShingle Special Issue: Papers from the 12th Workshop on Augmented Environments for Computer-Assisted Interventions
Xia, Wenyao
Chen, Elvis C.S.
Peters, Terry
Endoscopic image enhancement with noise suppression
title Endoscopic image enhancement with noise suppression
title_full Endoscopic image enhancement with noise suppression
title_fullStr Endoscopic image enhancement with noise suppression
title_full_unstemmed Endoscopic image enhancement with noise suppression
title_short Endoscopic image enhancement with noise suppression
title_sort endoscopic image enhancement with noise suppression
topic Special Issue: Papers from the 12th Workshop on Augmented Environments for Computer-Assisted Interventions
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6222180/
https://www.ncbi.nlm.nih.gov/pubmed/30464845
http://dx.doi.org/10.1049/htl.2018.5067
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