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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...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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Hindawi Publishing Corporation
2009
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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. |
format | Text |
id | pubmed-2669570 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
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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