Bayesian super-resolution in brain diffusion weighted magnetic resonance imaging (DW-MRI)

Juan S.A. Celis, Nelson F.T. Velasco, Julio E. Villalon-Reina, Paul M. Thompson, Eduardo C. Romero

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a Bayesian super resolution (SR) method obtains high resolution (HR) brain Diffusion-Weighted Magnetic Resonance Imaging (DMRI) images from degraded low resolution (LR) images. Under a Bayesian formulation, the unknown HR image, the acquisition process and the unknown parameters are modeled as stochastic processes. The likelihood model is modeled using a Gaussian distribution to estimate the error between the a linear representation and the observations. The prior is introduced as a Multivariate Gaussian Distribution, for which the inverse of the covariance matrix is approximated by Laplacian-like functions that model the local relationships, capturing thereby non-homogeneous relationships between neighbor intensities. Experimental results show the method outperforms the base line by 2.56 dB when using PSNR as a metric of quality in a set of 35 cases.

Original languageEnglish
Title of host publication12th International Symposium on Medical Information Processing and Analysis
EditorsEduardo Romero, Natasha Lepore, Jorge Brieva, Ignacio Larrabide
PublisherSPIE
ISBN (Electronic)9781510607781
DOIs
StatePublished - 2017
Externally publishedYes
Event12th International Symposium on Medical Information Processing and Analysis, SIPAIM 2016 - Tandil, Argentina
Duration: 5 Dec 20167 Dec 2016

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10160
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference12th International Symposium on Medical Information Processing and Analysis, SIPAIM 2016
Country/TerritoryArgentina
CityTandil
Period5/12/167/12/16

Keywords

  • Bayesian
  • Diffusion weighted magnetic resonance imaging
  • Image processing
  • Super resolution

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