BrainMask Volume Processing Tool
Segmentation of the brain from three-dimensional MR images is a crucial pre-processing step in morphological and volumetric brain studies. BrainMask implements a fully automatic brain segmentation algorithm that uses advanced "thresholding with morphology" and 3D edge detection algorithms. BrainMask demonstrates high segmentation accuracy. For a representative 26 datasets, the segmentation error averaged 3.4% ± 1.3% (Mikheev A et al. J Magn Reson Imag 27(6):1235-41;2008).
BrainMask includes NNN - a tool based on the algorithm developed by John Sled for correcting the intensity non-uniformity in MR data (Sled JG et al. IEEE Trans Med Imag 17(1):87-97;1998).
BrainMask also includes a versatile DICOM wiewer and allows to selectively load and organize DICOM images into 3D and 4D datasets.
BrainMask includes NNN - a tool based on the algorithm developed by John Sled for correcting the intensity non-uniformity in MR data (Sled JG et al. IEEE Trans Med Imag 17(1):87-97;1998).
BrainMask also includes a versatile DICOM wiewer and allows to selectively load and organize DICOM images into 3D and 4D datasets.
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