title: Comparison of tissue segmentation algorithms in neuroimage analysis software tools.
abstract: Accurate segmentation of different brain tissues is of much importance in magnetic resonance imaging. This paper presents a comparison of the existing segmentation algorithms that are deployed in the neuroimaging community as part of two widely used software packages. The results obtained in this comparison can be used to select the appropriate segmentation algorithm for the neuroimaging application of interest. In addition to the entire brain area, a comparison is carried out for the subcortical region of the brain in terms of its gray matter composition.
authors.affiliation: Electrical Engineering Department, University of Texas at Dallas, 800 W. Campbell Rd., Richardson, TX 75080, USA.
authors.forename: On
authors.initials: O
authors.lastname: Tsang
authors.forename: Ali
authors.initials: A
authors.lastname: Gholipour
authors.forename: Nasser
authors.initials: N
authors.lastname: Kehtarnavaz
authors.forename: Kaundinya
authors.initials: K
authors.lastname: Gopinath
authors.forename: Richard
authors.initials: R
authors.lastname: Briggs
authors.forename: Issa
authors.initials: I
authors.lastname: Panahi
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology* / Q000473:pathology / Q000502:physiology; D003196:Computer Graphics; D003201:Computers; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008390:Markov Chains; D019047:Phantoms, Imaging; D011381:Programming Languages; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software