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Author Steudel, A. ♦ Ortmann, S. ♦ Glesner, M.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©1995
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Biomedical imaging ♦ Image coding ♦ Neural networks ♦ Medical diagnostic imaging ♦ Back ♦ Artificial neural networks ♦ Digital images ♦ X-ray imaging ♦ Spatial resolution ♦ Image reconstruction
Abstract A nonlinear 5 layer artificial neural autoencoder network for image data compression is constructed and trained using the back propagation algorithm and medical CT images. The influence of linear and nonlinear pre/postprocessing operations is studied as well as an alternative compression scheme. Important implementational issues of neural networks are addressed as well as autoencoder issues. One of the results of this work is a compression/decompression tool that provides maximum flexibility and can be used independently from the training environment.
Description Author affiliation: Inst. of Microelectron. Syst., Darmstadt Univ. of Technol., Germany (Steudel, A.; Ortmann, S.; Glesner, M.)
ISBN 0818671262
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1995-09-17
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 830.71 kB
Page Count 6
Starting Page 571
Ending Page 576

Source: IEEE Xplore Digital Library