Title | GBM volumetry using the 3D Slicer medical image computing platform. |
Publication Type | Journal Article |
Year of Publication | 2013 |
Authors | Egger, J, Kapur, T, Fedorov, A, Pieper, S, Miller, JV, Veeraraghavan, H, Freisleben, B, Golby, AJ, Nimsky, C, Kikinis, R |
Journal | Sci Rep |
Volume | 3 |
Pagination | 1364 |
Date Published | 2013 |
ISSN | 2045-2322 |
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. |
DOI | 10.1038/srep01364 |
Alternate Journal | Sci Rep |
PubMed ID | 23455483 |
PubMed Central ID | PMC3586703 |
Grant List | P41 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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