Surgical Planning Laboratory - Brigham & Women's Hospital - Boston, Massachusetts USA - a teaching affiliate of Harvard Medical School

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Automated Segmentation of Brain Tumors

Institution:
1Surgical Planning Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
2Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
3Computational Radiology Laboratory, Departments of Radiology, Children’s Hospital and Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA.
4Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Publisher:
SPL
Publication Date:
Dec-2007
Citation:
SPL 2007 Dec;
Keywords:
automated segmentation, manual segmentation, Brain Tumor, reproducibility
Appears in Collections:
SPL, CRL, Download Data, NAC, NCIGT, SLICER
Sponsors:
P41 RR013218/RR/NCRR NIH HHS/United States
P01 CA067165/CA/NCI NIH HHS/United States
R01 RR011747/RR/NCRR NIH HHS/United States
Generated Citation:
Kaus M.R., Warfield S.K., Nabavi A., Black P.M., Jolesz F.A., Kikinis R. Automated Segmentation of Brain Tumors. SPL 2007 Dec;
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An automated brain tumor segmentation method was developed and validated against manual segmentation with three-dimensional magnetic resonance images in 10 patients with meningiomas and low-grade gliomas, Kaus et al., 2001. The automated method (operator time, 5-10 minutes) allowed rapid identification of brain and tumor tissue with an accuracy and reproducibility comparable to those of manual segmentation (operator time, 3-5 hours), making automated segmentation practical for low-grade gliomas and meningiomas. We make available the image datasets used in our study, results of our algorithms, and open source software (3D Slicer) for data access and processing to interested parties, as a free service.

Additional Material
2 Files (167MB)
Expert-table.jpg (270.615kB) Tumorbase.zip (167MB)