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Titolo:
Three-dimensional multimodal brain warping using the demons algorithm and adaptive intensity corrections
Autore:
Guimond, A; Roche, A; Ayache, N; Meunier, J;
Indirizzi:
INRIA, Projet Epidaure, F-06902 Sophia Antipolis, France INRIA Sophia Antipolis France F-06902 , F-06902 Sophia Antipolis, France Univ Montreal, Dept Informat & Rech Operat, Montreal, PQ H3C 3J7, Canada Univ Montreal Montreal PQ Canada H3C 3J7 at, Montreal, PQ H3C 3J7, Canada
Titolo Testata:
IEEE TRANSACTIONS ON MEDICAL IMAGING
fascicolo: 1, volume: 20, anno: 2001,
pagine: 58 - 69
SICI:
0278-0062(200101)20:1<58:TMBWUT>2.0.ZU;2-Z
Fonte:
ISI
Lingua:
ENG
Soggetto:
IMAGE REGISTRATION; MUTUAL INFORMATION; MAXIMIZATION;
Keywords:
elastic registration; intensity correction; medical imaging; multimodality; robust estimation;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Clinical Medicine
Engineering, Computing & Technology
Citazioni:
24
Recensione:
Indirizzi per estratti:
Indirizzo: Guimond, A Brigham & Womens Hosp, Ctr Neurol Imaging, 221 Longwood Ave, Boston, MA 02115 USA Brigham & Womens Hosp 221 Longwood Ave Boston MA USA 02115 USA
Citazione:
A. Guimond et al., "Three-dimensional multimodal brain warping using the demons algorithm and adaptive intensity corrections", IEEE MED IM, 20(1), 2001, pp. 58-69

Abstract

This paper presents an original method for three-dimensional elastic registration of multimodal images. We propose to make use of a scheme that iterates between correcting for intensity differences between images and performing standard monomodal registration. The care of our contribution resides in providing a method that finds the transformation that maps the intensities of one image to those of another, It makes the assumption that there are at most two functional dependencies between the intensities of structures present in the images to register, and relies on robust estimation techniques to evaluate these functions. We provide results showing successful registration between several imaging modalities involving segmentations, T1 magnetic resonance (MR), T2 MR, proton density (PD) MR and computed tomography (CT), We also argue that our intensity modeling mag be more appropriate thanmutual information (MI) in the contest of evaluating high-dimensional deformations, as it puts more constraints on the parameters to be estimated and, thus, permits a better search of the parameter space.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 31/03/20 alle ore 04:35:53