Statistical aspects of parallel imaging reconstruction. Academic Article uri icon

Overview

abstract

  • A statistical interpretation of existing parallel magnetic resonance imaging methods reveals that the underlying noise model is of additive independent Gaussian noise. In reality MR imaging processes suffer from a variety of noise, errors and other uncertainties. A careful statistical analysis of these uncertainties can potentially allow significant improvement of the reconstruction process. In this paper we present such an analysis and describe a few very recent approaches to handle these statistical models. We show examples of simulation and in vivo reconstructed data which demonstrate the potential of the statistical approach.

publication date

  • January 1, 2006

Research

keywords

  • Algorithms
  • Image Enhancement
  • Image Interpretation, Computer-Assisted
  • Magnetic Resonance Imaging
  • Signal Processing, Computer-Assisted

Identity

Scopus Document Identifier

  • 34047122206

Digital Object Identifier (DOI)

  • 10.1109/IEMBS.2006.259763

PubMed ID

  • 17946826

Additional Document Info

volume

  • 2006