Fast, accurate, and reproducible automatic segmentation of the brain in T1-weighted volume MRI data.
A new fast automated algorithm has been developed to segment the brain from T1-weighted volume MR images. The algorithm uses automated thresholding and morphological operations. It is fully three-dimensional and therefore independent of scan orientation. The validity and the performance of the algorithm were evaluated by comparing the automatically calculated brain volume with semi-automated measurements in 10 subjects, by calculating the brain volume from repeated scans in another 10 subjects, and by visual inspection. The mean and standard deviation of the difference between semi-automated and automated measurements were 0.56% and 2.8% of the mean brain volume, respectively, which is within inter-observer variability of the semi-automated method. The mean and standard deviation of the difference between the total volumes calculated from repeated scans were 0.40% and 1.2% of the mean brain volume, respectively. Good results were also obtained from a scan of abnormal brains.
Lemieux
L
L
Department of Clinical Neurology, University College London, United Kingdom. llemieux@ion.ucl.ac.uk
Hagemann
G
G
Krakow
K
K
Woermann
F G
FG
D000328:Adult; D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000033:anatomy & histology*; D002508:Cephalometry; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation*; D008279:Magnetic Resonance Imaging / Q000295:instrumentation*; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results