Neural net computing for biomedical image processing

Anke Meyer-Baese

doi:10.1117/12.342897

22 March 1999 Neural net computing for biomedical image processing

Anke Meyer-Baese

Proceedings Volume 3722, Applications and Science of Computational Intelligence II; (1999) https://doi.org/10.1117/12.342897
Event: AeroSense '99, 1999, Orlando, FL, United States

Abstract

In this paper we describe some of the most important types of neural networks applied in biomedical image processing. The networks described are variations of well-known architectures but are including image-relevant features in their structure. Convolutional neural networks, modified Hopfield networks, regularization networks and nonlinear principal component analysis neural networks are successfully applied in biomedical image classification, restoration and compression.

Citation Download Citation

Anke Meyer-Baese "Neural net computing for biomedical image processing", Proc. SPIE 3722, Applications and Science of Computational Intelligence II, (22 March 1999); https://doi.org/10.1117/12.342897

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