A Hierarchical Algorithm for MR Brain Image Parcellation

We introduce an algorithm for segmenting brain magnetic resonance (MR) images into anatomical compartments such as the major tissue classes and neuro-anatomical structures of the gray matter. The algorithm is guided by prior information represented within a tree structure. The tree mirrors the hiera...

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Veröffentlicht in:	IEEE transactions on medical imaging 2007-09, Vol.26 (9), p.1201-1212
Hauptverfasser:	Pohl, K.M., Bouix, S., Nakamura, M., Rohlfing, T., McCarley, R.W., Kikinis, R., Grimson, W.E.L., Shenton, M.E., Wells, W.M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Affective Disorders, Psychotic - diagnosis Algorithms Artificial Intelligence Automatic segmentation Biomedical imaging Brain Brain - pathology Computer science Computer Simulation data tree expectation-maximization Hospitals Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image segmentation Laboratories Magnetic Resonance Imaging - methods Models, Neurological MRI Neuroscience parcellation Pattern Recognition, Automated - methods Reproducibility of Results Schizophrenia Schizophrenia - diagnosis Sensitivity and Specificity statistical group comparison study Studies Surgery Tree data structures
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