Modelling of medical magnetic-resonance-imaging signals

Author

de Beer, R. ; Marseille, G.J. ; Mehlkopf, A.F. ; van Ormondt, D. ; Wajer, F.T.A.W.

Author_Institution

Dept. of Appl. Phys., Delft Univ. of Technol., Netherlands

Volume

141

Issue

1

fYear

1994

fDate

2/1/1994 12:00:00 AM

Firstpage

71

Lastpage

75

Abstract

Estimation of images of metabolite concentrations in humans from in vivo magnetic-resonance signals is considered. A 3-dimensional model function is set up in which one dimension pertains to the time domain, and the other two to the reciprocal spatial domain. In the various stages of the estimation fast Fourier transforms and a state-space approach are applied. The computation time can be limited by correcting magnetic-field inhomogeneity and classifying the various parts of the image with the aid of artificial neural networks. In difficult cases spectroscopic prior knowledge is invoked in conjunction with nonlinear least-squares fitting

Keywords

biomedical NMR; fast Fourier transforms; image recognition; image reconstruction; least squares approximations; medical image processing; neural nets; patient diagnosis; state-space methods; time-domain analysis; 3D model function; artificial neural networks; computation time; fast Fourier transforms; humans; in vivo magnetic-resonance signals; magnetic-field inhomogeneity; medical magnetic-resonance-imaging signals; metabolite concentrations; nonlinear least-squares fitting; reciprocal spatial domain; spectroscopic prior knowledge; state-space approach; time domain;

fLanguage

English

Journal_Title

Vision, Image and Signal Processing, IEE Proceedings -

Publisher

iet

ISSN

1350-245X

Type

jour

DOI

10.1049/ip-vis:19949914

Filename

278138