title: Decomposition of three-dimensional medical images into visual patterns.
abstract: In this paper, we present a method for the decomposition of a volumetric image into its most relevant visual patterns, which we define as features associated to local energy maxima of the image. The method involves the clustering of a set of predefined bandpass energy filters according to their ability to segregate the different features in the image, thus generating a set of composite-feature detectors tuned to the specific visual patterns present in the data. Clustering is based on a measure of statistical dependence between pairs of frequency features. We will illustrate the applicability of the method to the initialization of a three-dimensional geodesic active model.
authors.affiliation: Department of Electronics and Computer Science, Universidade de Santiago de Compostela, Campus Universitario Sur, s/n, 15782 Santiago de Compostela, Spain. rdosil@usc.es
authors.forename: Raquel
authors.initials: R
authors.lastname: Dosil
authors.forename: Xosé M
authors.initials: XM
authors.lastname: Pardo
authors.forename: Xosé R
authors.initials: XR
authors.lastname: Fdez-Vidal
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology; D003196:Computer Graphics; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014584:User-Computer Interface