Neural net computing for biomedical image processing
Anke Meyer‐Baese · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1999
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.