Cargando…
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...
Autores principales: | , , , , , , , , , |
---|---|
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 |
_version_ | 1782261343722668032 |
---|---|
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. |
format | Online Article Text |
id | pubmed-3586703 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT eggerjan gbmvolumetryusingthe3dslicermedicalimagecomputingplatform AT kapurtina gbmvolumetryusingthe3dslicermedicalimagecomputingplatform AT fedorovandriy gbmvolumetryusingthe3dslicermedicalimagecomputingplatform AT piepersteve gbmvolumetryusingthe3dslicermedicalimagecomputingplatform AT millerjamesv gbmvolumetryusingthe3dslicermedicalimagecomputingplatform AT veeraraghavanharini gbmvolumetryusingthe3dslicermedicalimagecomputingplatform AT freislebenbernd gbmvolumetryusingthe3dslicermedicalimagecomputingplatform AT golbyalexandraj gbmvolumetryusingthe3dslicermedicalimagecomputingplatform AT nimskychristopher gbmvolumetryusingthe3dslicermedicalimagecomputingplatform AT kikinisron gbmvolumetryusingthe3dslicermedicalimagecomputingplatform |