21 May 1999 Fast automatic segmentation of the brain in T1-weighted volume MRI data
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Abstract
A fully automated algorithm was developed to segment the brain from T1-weighted volume MR images. Automatic non- uniformity correction is performed prior to segmentation. The segmentation algorithm is based on automatic thresholding and morphological operations. It is fully 3D and therefore independent of scan orientation. The validity and performance of the algorithm were evaluated by comparing the automatically calculated brain volume with semi- automated measurements in 10 subjects. The amount of non- brain tissue included in the automatic segmentation was calculated. To test reproducibility, the brain volume was calculated in repeated scans in another 10 subjects. The mean and standard deviation of the difference between the semi-automated and automated measurements were 0.6% and 2.8% of the mean brain volume, respectively, which is within the inter-observer variability of the semi-automatic method. The mean amount of non-brain tissue contained in the segmented brain mask was 0.3% of the mean brain volume, with a standard deviation of 0.2%. The mean and standard deviation of the difference between the total volumes calculated from repeated scans were 0.4% and 1.2% of the mean brain volume, respectively.
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Louis Lemieux, Georg Hagemann, Karsten Krakow, Friedrich G. Woermann, "Fast automatic segmentation of the brain in T1-weighted volume MRI data", Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); doi: 10.1117/12.348561; https://doi.org/10.1117/12.348561
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