Statistical Methods in the Fourier Domain to Enhance and Classify Images

Functional neuroimaging is a powerful biological tool to investigate the regions of the brain responsible for performing diflerent mental functions. The traditional anterpretation method is statistical analysis in the spatial domain, which is computationally expensive. In this paper we present a hybrid wavelet/neural network scheme to analyze functional brain images. Features are extracted in the Wavelet domain and then fed t o a neural network for detection. The proposed method is examined by exploring the diflerences between Positron Emission Tomography (PET) images acquired under different ezperimental conditions during a tone recognition task. The performance shows its potential in the fast developing functional neuroimaging area.

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Hybrid wavelet/neural network analysis of differences in functional brain images

Ma¹,

Holcomb²,

Morris³

IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339)

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Statistical Methods in the Fourier Domain to Enhance and Classify Images

Cited by 1 publication

References 28 publications

Hybrid wavelet/neural network analysis of differences in functional brain images

Hybrid wavelet/neural network analysis of differences in functional brain images

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