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Markerless Lung Tumor Motion Tracking by Dynamic Decomposition of X-Ray Image Intensity

We propose a new markerless tracking technique of lung tumor motion by using an X-ray fluoroscopic image sequence for real-time image-guided radiation therapy (IGRT). A core innovation of the new technique is to extract a moving tumor intensity component from the fluoroscopic image intensity. The fl...

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Autores principales: Homma, Noriyasu, Takai, Yoshihiro, Endo, Haruna, Ichiji, Kei, Narita, Yuichiro, Zhang, Xiaoyong, Sakai, Masao, Osanai, Makoto, Abe, Makoto, Sugita, Norihiro, Yoshizawa, Makoto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4782636/
https://www.ncbi.nlm.nih.gov/pubmed/27006911
http://dx.doi.org/10.1155/2013/340821
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author Homma, Noriyasu
Takai, Yoshihiro
Endo, Haruna
Ichiji, Kei
Narita, Yuichiro
Zhang, Xiaoyong
Sakai, Masao
Osanai, Makoto
Abe, Makoto
Sugita, Norihiro
Yoshizawa, Makoto
author_facet Homma, Noriyasu
Takai, Yoshihiro
Endo, Haruna
Ichiji, Kei
Narita, Yuichiro
Zhang, Xiaoyong
Sakai, Masao
Osanai, Makoto
Abe, Makoto
Sugita, Norihiro
Yoshizawa, Makoto
author_sort Homma, Noriyasu
collection PubMed
description We propose a new markerless tracking technique of lung tumor motion by using an X-ray fluoroscopic image sequence for real-time image-guided radiation therapy (IGRT). A core innovation of the new technique is to extract a moving tumor intensity component from the fluoroscopic image intensity. The fluoroscopic intensity is the superimposition of intensity components of all the structures passed through by the X-ray. The tumor can then be extracted by decomposing the fluoroscopic intensity into the tumor intensity component and the others. The decomposition problem for more than two structures is ill posed, but it can be transformed into a well-posed one by temporally accumulating constraints that must be satisfied by the decomposed moving tumor component and the rest of the intensity components. The extracted tumor image can then be used to achieve accurate tumor motion tracking without implanted markers that are widely used in the current tracking techniques. The performance evaluation showed that the extraction error was sufficiently small and the extracted tumor tracking achieved a high and sufficient accuracy less than 1 mm for clinical datasets. These results clearly demonstrate the usefulness of the proposed method for markerless tumor motion tracking.
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spelling pubmed-47826362016-03-22 Markerless Lung Tumor Motion Tracking by Dynamic Decomposition of X-Ray Image Intensity Homma, Noriyasu Takai, Yoshihiro Endo, Haruna Ichiji, Kei Narita, Yuichiro Zhang, Xiaoyong Sakai, Masao Osanai, Makoto Abe, Makoto Sugita, Norihiro Yoshizawa, Makoto J Med Eng Research Article We propose a new markerless tracking technique of lung tumor motion by using an X-ray fluoroscopic image sequence for real-time image-guided radiation therapy (IGRT). A core innovation of the new technique is to extract a moving tumor intensity component from the fluoroscopic image intensity. The fluoroscopic intensity is the superimposition of intensity components of all the structures passed through by the X-ray. The tumor can then be extracted by decomposing the fluoroscopic intensity into the tumor intensity component and the others. The decomposition problem for more than two structures is ill posed, but it can be transformed into a well-posed one by temporally accumulating constraints that must be satisfied by the decomposed moving tumor component and the rest of the intensity components. The extracted tumor image can then be used to achieve accurate tumor motion tracking without implanted markers that are widely used in the current tracking techniques. The performance evaluation showed that the extraction error was sufficiently small and the extracted tumor tracking achieved a high and sufficient accuracy less than 1 mm for clinical datasets. These results clearly demonstrate the usefulness of the proposed method for markerless tumor motion tracking. Hindawi Publishing Corporation 2013 2013-12-08 /pmc/articles/PMC4782636/ /pubmed/27006911 http://dx.doi.org/10.1155/2013/340821 Text en Copyright © 2013 Noriyasu Homma 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
Homma, Noriyasu
Takai, Yoshihiro
Endo, Haruna
Ichiji, Kei
Narita, Yuichiro
Zhang, Xiaoyong
Sakai, Masao
Osanai, Makoto
Abe, Makoto
Sugita, Norihiro
Yoshizawa, Makoto
Markerless Lung Tumor Motion Tracking by Dynamic Decomposition of X-Ray Image Intensity
title Markerless Lung Tumor Motion Tracking by Dynamic Decomposition of X-Ray Image Intensity
title_full Markerless Lung Tumor Motion Tracking by Dynamic Decomposition of X-Ray Image Intensity
title_fullStr Markerless Lung Tumor Motion Tracking by Dynamic Decomposition of X-Ray Image Intensity
title_full_unstemmed Markerless Lung Tumor Motion Tracking by Dynamic Decomposition of X-Ray Image Intensity
title_short Markerless Lung Tumor Motion Tracking by Dynamic Decomposition of X-Ray Image Intensity
title_sort markerless lung tumor motion tracking by dynamic decomposition of x-ray image intensity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4782636/
https://www.ncbi.nlm.nih.gov/pubmed/27006911
http://dx.doi.org/10.1155/2013/340821
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