Application of artificial neural networks for tissue classification from multispectral magnetic resonance images of the head

Author

Schellenberg, John D. ; Naylor, William C. ; Clarke, Laurence P.

Author_Institution

Univ. of South Florida, Tampa, FL, USA

fYear

1990

fDate

3-6 Jun 1990

Firstpage

350

Lastpage

357

Abstract

The suitability of artificial neural networks (ANNs) for the classification of multispectral magnetic resonance images (MSMRI) is explored. MSMRI feature space distributions of various tissues and phantoms were examined to determine if the data is more suitable for ANN classification, as opposed to classical Bayesian approaches for intensity-based classification. Additionally, MSMRI normalization methods were investigated to determine suitability for improving feature space distributions independent of classification methods

Keywords

biomedical NMR; medical diagnostic computing; neural nets; artificial neural networks; classical Bayesian approaches; feature space distributions; head; intensity-based classification; multispectral magnetic resonance images; normalization methods; phantoms; tissue classification; Artificial neural networks; Bayesian methods; Coils; Head; High-resolution imaging; Image resolution; Imaging phantoms; Magnetic resonance imaging; Radio frequency; Statistical distributions;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer-Based Medical Systems, 1990., Proceedings of Third Annual IEEE Symposium on

Conference_Location

Chapel Hill, NC

Print_ISBN

0-8186-9040-2

Type

conf

DOI

10.1109/CBMSYS.1990.109419

Filename

109419