@article {865,
	title = {GBM volumetry using the 3D Slicer medical image computing platform.},
	journal = {Sci Rep},
	volume = {3},
	year = {2013},
	month = {2013},
	pages = {1364},
	abstract = {<p>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 {\textpm} 5.23\% and a Hausdorff Distance of 2.32 {\textpm} 5.23 mm.</p>},
	issn = {2045-2322},
	doi = {10.1038/srep01364},
	author = {Egger, Jan and Kapur, Tina and Fedorov, Andriy and Pieper, Steve and Miller, James V and Veeraraghavan, Harini and Freisleben, Bernd and Golby, Alexandra J and Nimsky, Christopher and Kikinis, Ron}
}
