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22 March 1999 Neural net computing for biomedical image processing
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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.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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