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GBM volumetry using the 3D Slicer medical image computing platform.

Submitted by holger on Wed, 2013/07/10 - 11:40
TitleGBM volumetry using the 3D Slicer medical image computing platform.
Publication TypeJournal Article
Year of Publication2013
AuthorsEgger, J, Kapur, T, Fedorov, A, Pieper, S, Miller, JV, Veeraraghavan, H, Freisleben, B, Golby, AJ, Nimsky, C, Kikinis, R
JournalSci Rep
Volume3
Pagination1364
Date Published2013
ISSN2045-2322
Abstract

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.

DOI10.1038/srep01364
Alternate JournalSci Rep
PubMed ID23455483
PubMed Central IDPMC3586703
Grant ListP41 EB015902 / EB / NIBIB NIH HHS / United States
P41EB015898 / EB / NIBIB NIH HHS / United States
P41RR019703 / RR / NCRR NIH HHS / United States
R03EB013792 / EB / NIBIB NIH HHS / United States
U54 EB005149 / EB / NIBIB NIH HHS / United States
U54EB005149 / EB / NIBIB NIH HHS / United States
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