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Automated Segmentation of Brain Tumors
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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 December; |
Keywords: |
automated segmentation, manual segmentation, brain tumor, reproducibility |
Appears in Collections: |
SPL, CRL, Download Data, NAC, NCIGT, SLICER |
Sponsors: |
NIH P01 CA67165 NIH R01 RR11747 NIH P41 RR13218 |
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 December; |
| Downloaded: | 3598 times. [view map] |
| Export citation: |
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)