title: Automated segmentation of MR images of brain tumors.
abstract: 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.
authors.affiliation: Surgical Planning Laboratory, Depts of Radiology, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA.
authors.forename: M R
authors.initials: MR
authors.lastname: Kaus
authors.forename: S K
authors.initials: SK
authors.lastname: Warfield
authors.forename: A
authors.initials: A
authors.lastname: Nabavi
authors.forename: P M
authors.initials: PM
authors.lastname: Black
authors.forename: F A
authors.initials: FA
authors.lastname: Jolesz
authors.forename: R
authors.initials: R
authors.lastname: Kikinis
mesh_terms: D001921:Brain / Q000473:pathology*; D001932:Brain Neoplasms / Q000473:pathology*; D005910:Glioma / Q000473:pathology*; D006801:Humans; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging; D008577:Meningeal Neoplasms / Q000473:pathology*; D008579:Meningioma / Q000473:pathology*; D015588:Observer Variation; D015203:Reproducibility of Results