Title :
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
fDate :
2/1/1994 12:00:00 AM
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;
Journal_Title :
Vision, Image and Signal Processing, IEE Proceedings -
DOI :
10.1049/ip-vis:19949914
