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Titolo: A joint physicsbased statistical deformable model for multimodal brain image analysis
Autore: Nikou, C; Bueno, G; Heitz, F; Armspach, JP;
 Indirizzi:
 Univ Strasbourg 1, Lab Sci Image Informat & Teledetect, UPRESA 7005, F67400 Illkirch Graffenstaden, France Univ Strasbourg 1 Illkirch Graffenstaden France F67400 enstaden, France Univ Strasbourg 1, Inst Phys Biol, Fac Med, CNRS,UPRESA 7004, F67400 Illkirch Graffenstaden, France Univ Strasbourg 1 Illkirch Graffenstaden France F67400 enstaden, France
 Titolo Testata:
 IEEE TRANSACTIONS ON MEDICAL IMAGING
fascicolo: 10,
volume: 20,
anno: 2001,
pagine: 1026  1037
 SICI:
 02780062(200110)20:10<1026:AJPSDM>2.0.ZU;2J
 Fonte:
 ISI
 Lingua:
 ENG
 Soggetto:
 SEGMENTATION; REGISTRATION; DEFORMATIONS; SURFACES; ATLAS;
 Keywords:
 brain isolation; image registration; magnetic resonance imaging (MRI); physically based deformable model; single photon emission computed tomography (SPECT); statistical shape models;
 Tipo documento:
 Article
 Natura:
 Periodico
 Settore Disciplinare:
 Clinical Medicine
 Engineering, Computing & Technology
 Citazioni:
 26
 Recensione:
 Indirizzi per estratti:
 Indirizzo: Heitz, F Univ Strasbourg 1, Lab Sci Image Informat & Teledetect, UPRESA 7005, 4 Bd Sebastien Brant, F67400 Illkirch Graffenstaden, France Univ Strasbourg 1 4 Bd Sebastien Brant Illkirch Graffenstaden France F67400



 Citazione:
 C. Nikou et al., "A joint physicsbased statistical deformable model for multimodal brain image analysis", IEEE MED IM, 20(10), 2001, pp. 10261037
Abstract
A probabilistic deformable, model for the representation of multiple brainstructures is described. The statistically learned deformable model! represents the relative location of different anatomical surfaces in brain magnetic resonance images (MRIs) and accommodates their significant variability across different individuals. The surfaces of each anatomical structure areparameterized by the amplitudes of the vibration modes of a deformable spherical mesh. For a given MRI in the training set, a vector containing the largest vibration modes describing the different deformable surfaces is created. This random vector is statistically constrained by retaining the most significant variation modes of its KarhunenLoeve expansion on the trainingpopulation. By these means, the conjunction of surfaces are deformed according to the anatomical variability observed in the training set. Two applications of the joint probabilistic deformable model are presented: isolationof the brain from MRI using the probabilistic constraints embedded in the model; and deformable modelbased registration of threedimensional multimodal (magnetic resonance/single photon emission computed tomography) brain images without removing nonbrain structures. The multiobject deformable model may be considered as a first step toward the development of a general purpose probabilistic anatomical atlas of the brain.
ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 25/01/20 alle ore 07:16:14