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Temporal Matching in Endoscopic Images for Remote-Controlled Robotic Surgery

Temporal matching is applied in the frame of the formation of high-level entities in remote-controlled robotic surgery. The objective is to track tumor boundaries over time to improve the segmentation stage in each image of the sequence to facilitate the tracking and localization of the tumor. It ma...

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Detalles Bibliográficos
Autores principales: Gu, Jia, Wolters, Rolf, Gustafsson, Ulf
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2669570/
https://www.ncbi.nlm.nih.gov/pubmed/19390628
http://dx.doi.org/10.1155/2009/627625
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author Gu, Jia
Wolters, Rolf
Gustafsson, Ulf
author_facet Gu, Jia
Wolters, Rolf
Gustafsson, Ulf
author_sort Gu, Jia
collection PubMed
description Temporal matching is applied in the frame of the formation of high-level entities in remote-controlled robotic surgery. The objective is to track tumor boundaries over time to improve the segmentation stage in each image of the sequence to facilitate the tracking and localization of the tumor. It makes use of an attributed string matching technique to find the correspondence between tumor boundaries over time. Relationships are then exploited to reconstitute the tumor boundaries and remove the inconsistencies coming from the detection errors. Input data are free form shapes of different length representing the tumor boundary, extracted at a previous stage.
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spelling pubmed-26695702009-04-23 Temporal Matching in Endoscopic Images for Remote-Controlled Robotic Surgery Gu, Jia Wolters, Rolf Gustafsson, Ulf Int J Telemed Appl Research Article Temporal matching is applied in the frame of the formation of high-level entities in remote-controlled robotic surgery. The objective is to track tumor boundaries over time to improve the segmentation stage in each image of the sequence to facilitate the tracking and localization of the tumor. It makes use of an attributed string matching technique to find the correspondence between tumor boundaries over time. Relationships are then exploited to reconstitute the tumor boundaries and remove the inconsistencies coming from the detection errors. Input data are free form shapes of different length representing the tumor boundary, extracted at a previous stage. Hindawi Publishing Corporation 2009 2009-04-15 /pmc/articles/PMC2669570/ /pubmed/19390628 http://dx.doi.org/10.1155/2009/627625 Text en Copyright © 2009 Jia Gu et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Gu, Jia
Wolters, Rolf
Gustafsson, Ulf
Temporal Matching in Endoscopic Images for Remote-Controlled Robotic Surgery
title Temporal Matching in Endoscopic Images for Remote-Controlled Robotic Surgery
title_full Temporal Matching in Endoscopic Images for Remote-Controlled Robotic Surgery
title_fullStr Temporal Matching in Endoscopic Images for Remote-Controlled Robotic Surgery
title_full_unstemmed Temporal Matching in Endoscopic Images for Remote-Controlled Robotic Surgery
title_short Temporal Matching in Endoscopic Images for Remote-Controlled Robotic Surgery
title_sort temporal matching in endoscopic images for remote-controlled robotic surgery
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2669570/
https://www.ncbi.nlm.nih.gov/pubmed/19390628
http://dx.doi.org/10.1155/2009/627625
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