Estimation of the glucose metabolism from dynamic PET-scans using neural networks

Author

Svarer, Claus ; Law, Ian ; Holm, Søren ; Mørch, Niels ; Paulson, Olaf ; Hansen, Lars Kai ; Fog, Torben

Author_Institution

Dept. of Neurology, Nat. Univ. Hospital, Copenhagen, Denmark

fYear

1995

fDate

31 Aug-2 Sep 1995

Firstpage

439

Lastpage

448

Abstract

A method for fast pixel by pixel estimation of the glucose metabolism in the brain using the tracer [¹⁸F]fluorodeoxy-glucose in dynamic positron emission tomography (PET)-scan data is described. A neural network is trained to estimate the glucose metabolism on data generated by direct fitting of the rate constants in Sokoloff´s model. The generalisation ability of the neural network is tested on data from subjects not included in the training set. This method can be used to estimate changes of the metabolism in different brain regions for subjects with serious brain disorders. By using the neural estimation procedure the processing time for a brain scan volume is reduced from 48 hours to 4 minutes

Keywords

brain; feedforward neural nets; learning (artificial intelligence); medical computing; pattern recognition; positron emission tomography; Sokoloff´s model; brain disorders; dynamic PET-scans; dynamic positron emission tomography; feedforward neural networks; fluorodeoxy-glucose; glucose metabolism; metabolism change estimation; Biochemistry; Biological neural networks; Blood; Image reconstruction; Kinetic theory; Nervous system; Neural networks; Positron emission tomography; Sugar; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks for Signal Processing [1995] V. Proceedings of the 1995 IEEE Workshop

Conference_Location

Cambridge, MA

Print_ISBN

0-7803-2739-X

Type

conf

DOI

10.1109/NNSP.1995.514918

Filename

514918