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GBM Volumetry using the 3D Slicer Medical Image Computing Platform

Volumetric change in glioblastoma multiforme (GBM) over time is a critical factor in treatment decisions. Typically, the tumor volume is computed on a slice-by-slice basis using MRI scans obtained at regular intervals. (3D)Slicer – a free platform for biomedical research – provides an alternative to...

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Autores principales: Egger, Jan, Kapur, Tina, Fedorov, Andriy, Pieper, Steve, Miller, James V., Veeraraghavan, Harini, Freisleben, Bernd, Golby, Alexandra J., Nimsky, Christopher, Kikinis, Ron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3586703/
https://www.ncbi.nlm.nih.gov/pubmed/23455483
http://dx.doi.org/10.1038/srep01364
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author Egger, Jan
Kapur, Tina
Fedorov, Andriy
Pieper, Steve
Miller, James V.
Veeraraghavan, Harini
Freisleben, Bernd
Golby, Alexandra J.
Nimsky, Christopher
Kikinis, Ron
author_facet Egger, Jan
Kapur, Tina
Fedorov, Andriy
Pieper, Steve
Miller, James V.
Veeraraghavan, Harini
Freisleben, Bernd
Golby, Alexandra J.
Nimsky, Christopher
Kikinis, Ron
author_sort Egger, Jan
collection PubMed
description Volumetric change in glioblastoma multiforme (GBM) over time is a critical factor in treatment decisions. Typically, the tumor volume is computed on a slice-by-slice basis using MRI scans obtained at regular intervals. (3D)Slicer – a free platform for biomedical research – provides an alternative to this manual slice-by-slice segmentation process, which is significantly faster and requires less user interaction. In this study, 4 physicians segmented GBMs in 10 patients, once using the competitive region-growing based GrowCut segmentation module of Slicer, and once purely by drawing boundaries completely manually on a slice-by-slice basis. Furthermore, we provide a variability analysis for three physicians for 12 GBMs. The time required for GrowCut segmentation was on an average 61% of the time required for a pure manual segmentation. A comparison of Slicer-based segmentation with manual slice-by-slice segmentation resulted in a Dice Similarity Coefficient of 88.43 ± 5.23% and a Hausdorff Distance of 2.32 ± 5.23 mm.
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spelling pubmed-35867032013-03-06 GBM Volumetry using the 3D Slicer Medical Image Computing Platform Egger, Jan Kapur, Tina Fedorov, Andriy Pieper, Steve Miller, James V. Veeraraghavan, Harini Freisleben, Bernd Golby, Alexandra J. Nimsky, Christopher Kikinis, Ron Sci Rep Article Volumetric change in glioblastoma multiforme (GBM) over time is a critical factor in treatment decisions. Typically, the tumor volume is computed on a slice-by-slice basis using MRI scans obtained at regular intervals. (3D)Slicer – a free platform for biomedical research – provides an alternative to this manual slice-by-slice segmentation process, which is significantly faster and requires less user interaction. In this study, 4 physicians segmented GBMs in 10 patients, once using the competitive region-growing based GrowCut segmentation module of Slicer, and once purely by drawing boundaries completely manually on a slice-by-slice basis. Furthermore, we provide a variability analysis for three physicians for 12 GBMs. The time required for GrowCut segmentation was on an average 61% of the time required for a pure manual segmentation. A comparison of Slicer-based segmentation with manual slice-by-slice segmentation resulted in a Dice Similarity Coefficient of 88.43 ± 5.23% and a Hausdorff Distance of 2.32 ± 5.23 mm. Nature Publishing Group 2013-03-04 /pmc/articles/PMC3586703/ /pubmed/23455483 http://dx.doi.org/10.1038/srep01364 Text en Copyright © 2013, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-sa/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareALike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/
spellingShingle Article
Egger, Jan
Kapur, Tina
Fedorov, Andriy
Pieper, Steve
Miller, James V.
Veeraraghavan, Harini
Freisleben, Bernd
Golby, Alexandra J.
Nimsky, Christopher
Kikinis, Ron
GBM Volumetry using the 3D Slicer Medical Image Computing Platform
title GBM Volumetry using the 3D Slicer Medical Image Computing Platform
title_full GBM Volumetry using the 3D Slicer Medical Image Computing Platform
title_fullStr GBM Volumetry using the 3D Slicer Medical Image Computing Platform
title_full_unstemmed GBM Volumetry using the 3D Slicer Medical Image Computing Platform
title_short GBM Volumetry using the 3D Slicer Medical Image Computing Platform
title_sort gbm volumetry using the 3d slicer medical image computing platform
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3586703/
https://www.ncbi.nlm.nih.gov/pubmed/23455483
http://dx.doi.org/10.1038/srep01364
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