title: A Bayesian approach for relaxation times estimation in MRI.
abstract: Relaxation time estimation in MRI field can be helpful in clinical diagnosis. In particular, T1 and T2 changes can be related to tissues modification, being an effective tool for detecting the presence of several pathologies and measure their development, thus their estimation is a useful research field. Currently, most techniques work pixel-wise, and transfer the noise reduction task to post processing filters. A novel method for estimating spin-spin and spin-lattice relaxation times is proposed. The approach exploits Markov Random Field theory for modeling the unknown data and implements an a posteriori estimator in the Bayesian framework. The effect is the joint parameters estimation and noise reduction. Proposed methodology, with respect to already existing techniques, is able to provide effective results while preserving details also in case of few acquisitions or severe signal to noise ratio. The algorithm has been tested on both simulated and real datasets.
authors.affiliation: Dipartimento di Ingegneria, Università di Napoli Parthenope, Italy. Electronic address: fabio.baselice@uniparthenope.it.
authors.forename: Fabio
authors.initials: F
authors.lastname: Baselice
authors.affiliation: Dipartimento di Scienze e Tecnologie, Università di Napoli Parthenope, Italy.
authors.forename: Giampaolo
authors.initials: G
authors.lastname: Ferraioli
authors.affiliation: Dipartimento di Ingegneria, Università di Napoli Parthenope, Italy.
authors.forename: Vito
authors.initials: V
authors.lastname: Pascazio
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D001921:Brain / Q000000981:diagnostic imaging / Q000473:pathology; D003198:Computer Simulation; D016208:Databases, Factual; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016013:Likelihood Functions; D008279:Magnetic Resonance Imaging; D008297:Male; D008390:Markov Chains; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D012044:Regression Analysis; D059629:Signal-To-Noise Ratio
keywords: Bayesian estimation theory; MRI relaxation times; Markov random fields; Relaxation times