title: Multiresolution hierarchical shape models in 3D subcortical brain structures.
abstract: Point distribution models (PDM) are one of the most extended methods to characterize the underlying population of set of samples, whose usefulness has been demonstrated in a wide variety of applications, including medical imaging. However, one important issue remains unsolved: the large number of training samples required. This problem becomes critical as the complexity of the problem increases, and the modeling of 3D multiobjects/organs represents one of the most challenging cases. Based on the 3D wavelet transform, this paper introduces a multiresolution hierarchical variant of PDM (MRH-PDM) able to efficiently characterize the different inter-object relationships, as well as the particular locality of each element separately. The significant advantage of this new method over two previous approaches in terms of accuracy has been successfully verified for the particular case of 3D subcortical brain structures.
authors.affiliation: Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Medical Center, Washington DC, USA. JCerrola@cnmc.com
authors.forename: Juan J
authors.initials: JJ
authors.lastname: Cerrolaza
authors.affiliation: Alma IT Systems, Barcelona, Spain.
authors.forename: Noemí Carranza
authors.initials: NC
authors.lastname: Herrezuelo
authors.affiliation: Public University of Navarra, Pamplona, Spain.
authors.forename: Arantxa
authors.initials: A
authors.lastname: Villanueva
authors.affiliation: Public University of Navarra, Pamplona, Spain.
authors.forename: Rafael
authors.initials: R
authors.lastname: Cabeza
authors.affiliation: Alma IT Systems, Barcelona, Spain.
authors.forename: Miguel Angel
authors.initials: MA
authors.lastname: González Ballester
authors.affiliation: Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Medical Center, Washington DC, USA.
authors.forename: Marius George
authors.initials: MG
authors.lastname: Linguraru
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D003198:Computer Simulation; 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*; D008953:Models, Anatomic; D008959:Models, Neurological; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity