title: A Novel Statistical Approach for Brain MR Images Segmentation Based on Relaxation Times.
abstract: Brain tissue segmentation in Magnetic Resonance Imaging is useful for a wide range of applications. Classical approaches exploit the gray levels image and implement criteria for differentiating regions. Within this paper a novel approach for brain tissue joint segmentation and classification is presented. Starting from the estimation of proton density and relaxation times, we propose a novel method for identifying the optimal decision regions. The approach exploits the statistical distribution of the involved signals in the complex domain. The technique, compared to classical threshold based ones, is able to globally improve the classification rate. The effectiveness of the approach is evaluated on both simulated and real datasets.
authors.affiliation: Dipartimento di Ingegneria, Università di Napoli Parthenope, Centro Direzionale di Napoli, Isola C4, 80143 Napoli, Italy.
authors.forename: Fabio
authors.identifier: 0000-0002-5964-8667
authors.initials: F
authors.lastname: Baselice
authors.affiliation: Dipartimento di Scienze e Tecnologie, Università di Napoli Parthenope, Centro Direzionale di Napoli, Isola C4, 80143 Napoli, Italy.
authors.forename: Giampaolo
authors.initials: G
authors.lastname: Ferraioli
authors.affiliation: Dipartimento di Ingegneria, Università di Napoli Parthenope, Centro Direzionale di Napoli, Isola C4, 80143 Napoli, Italy.
authors.forename: Vito
authors.initials: V
authors.lastname: Pascazio
mesh_terms: D001921:Brain / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D008962:Models, Theoretical; D011859:Radiography