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Automated Segmentation of MR Images of Brain Tumors
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Institution: |
Surgical Planning Laboratory, Depts of Radiology, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA. |
Publisher: |
Radiology |
Publication Date: |
Feb-2001 |
Volume Number: |
218 |
Issue Number: |
2 |
Pages: |
586-591 |
Citation: |
Radiology. 2001 Feb;218(2):586-91. |
PubMed ID: |
11161183 |
Appears in Collections: |
SPL, NAC, NCIGT, SLICER |
Sponsors: |
P41 RR13218 (RR) funded by NCRR R01 RR11747 (RR) funded by NCRR P01 CA67165 (CA) funded by NCI |
Generated Citation: |
Kaus M.R., Warfield S.K., Nabavi A., Black P.M., Jolesz F.A., Kikinis R. Automated Segmentation of MR Images of Brain Tumors. Radiology. 2001 Feb;218(2):586-91. PMID: 11161183. |
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| Paper: | Download, View online |
| Export citation: |
An automated brain tumor segmentation method was developed and validated against manual segmentation with three-dimensional magnetic resonance images in 20 patients with meningiomas and low-grade gliomas. 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. The automated tumor segmentation datasets are available to download.
Additional Material
1 File (393.86kB)
Kaus-Radiology2001-fig2.jpg (393.86kB)