title: 3D surface analysis and classification in neuroimaging segmentation.
abstract: This work emphasizes new algorithms for 3D edge and corner detection used in surface extraction and new concept of image segmentation in neuroimaging based on multidimensional shape analysis and classification. We propose using of NifTI standard for describing input data which enables interoperability and enhancement of existing computing tools used widely in neuroimaging research. In methods section we present our newly developed algorithm for 3D edge and corner detection, together with the algorithm for estimating local 3D shape. Surface of estimated shape is analyzed and segmented according to kernel shapes.
authors.affiliation: University of Zagreb, Faculty of Electrical Engineering and Computing, Department of Control and Computer Engineering, Zagreb, Croatia. martin.zagar@fer.hr
authors.forename: Martin
authors.initials: M
authors.lastname: Zagar
authors.forename: Hrvoje
authors.initials: H
authors.lastname: Mlinarić
authors.forename: Josip
authors.initials: J
authors.lastname: Knezović
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging; D013499:Surface Properties