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Homographic Patch Feature Transform: A Robustness Registration for Gastroscopic Surgery

Image registration is a key component of computer assistance in image guided surgery, and it is a challenging topic in endoscopic environments. In this study, we present a method for image registration named Homographic Patch Feature Transform (HPFT) to match gastroscopic images. HPFT can be used fo...

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Detalles Bibliográficos
Autores principales: Hu, Weiling, Zhang, Xu, Wang, Bin, Liu, Jiquan, Duan, Huilong, Dai, Ning, Si, Jianmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4824530/
https://www.ncbi.nlm.nih.gov/pubmed/27054567
http://dx.doi.org/10.1371/journal.pone.0153202
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author Hu, Weiling
Zhang, Xu
Wang, Bin
Liu, Jiquan
Duan, Huilong
Dai, Ning
Si, Jianmin
author_facet Hu, Weiling
Zhang, Xu
Wang, Bin
Liu, Jiquan
Duan, Huilong
Dai, Ning
Si, Jianmin
author_sort Hu, Weiling
collection PubMed
description Image registration is a key component of computer assistance in image guided surgery, and it is a challenging topic in endoscopic environments. In this study, we present a method for image registration named Homographic Patch Feature Transform (HPFT) to match gastroscopic images. HPFT can be used for tracking lesions and augmenting reality applications during gastroscopy. Furthermore, an overall evaluation scheme is proposed to validate the precision, robustness and uniformity of the registration results, which provides a standard for rejection of false matching pairs from corresponding results. Finally, HPFT is applied for processing in vivo gastroscopic data. The experimental results show that HPFT has stable performance in gastroscopic applications.
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spelling pubmed-48245302016-04-22 Homographic Patch Feature Transform: A Robustness Registration for Gastroscopic Surgery Hu, Weiling Zhang, Xu Wang, Bin Liu, Jiquan Duan, Huilong Dai, Ning Si, Jianmin PLoS One Research Article Image registration is a key component of computer assistance in image guided surgery, and it is a challenging topic in endoscopic environments. In this study, we present a method for image registration named Homographic Patch Feature Transform (HPFT) to match gastroscopic images. HPFT can be used for tracking lesions and augmenting reality applications during gastroscopy. Furthermore, an overall evaluation scheme is proposed to validate the precision, robustness and uniformity of the registration results, which provides a standard for rejection of false matching pairs from corresponding results. Finally, HPFT is applied for processing in vivo gastroscopic data. The experimental results show that HPFT has stable performance in gastroscopic applications. Public Library of Science 2016-04-07 /pmc/articles/PMC4824530/ /pubmed/27054567 http://dx.doi.org/10.1371/journal.pone.0153202 Text en © 2016 Hu et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hu, Weiling
Zhang, Xu
Wang, Bin
Liu, Jiquan
Duan, Huilong
Dai, Ning
Si, Jianmin
Homographic Patch Feature Transform: A Robustness Registration for Gastroscopic Surgery
title Homographic Patch Feature Transform: A Robustness Registration for Gastroscopic Surgery
title_full Homographic Patch Feature Transform: A Robustness Registration for Gastroscopic Surgery
title_fullStr Homographic Patch Feature Transform: A Robustness Registration for Gastroscopic Surgery
title_full_unstemmed Homographic Patch Feature Transform: A Robustness Registration for Gastroscopic Surgery
title_short Homographic Patch Feature Transform: A Robustness Registration for Gastroscopic Surgery
title_sort homographic patch feature transform: a robustness registration for gastroscopic surgery
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4824530/
https://www.ncbi.nlm.nih.gov/pubmed/27054567
http://dx.doi.org/10.1371/journal.pone.0153202
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