Backpropagation Neural Network Implementation for Medical Image Compression
Author
Source
Journal of Applied Mathematics
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-31
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Medical images require compression, before transmission or storage, due to constrained bandwidth and storage capacity.
An ideal image compression system must yield high-quality compressed image with high compression ratio.
In this paper, Haar wavelet transform and discrete cosine transform are considered and a neural network is trained to relate the X-ray image contents to their ideal compression method and their optimum compression ratio.
American Psychological Association (APA)
Dimililer, Kamil. 2013. Backpropagation Neural Network Implementation for Medical Image Compression. Journal of Applied Mathematics،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-472771
Modern Language Association (MLA)
Dimililer, Kamil. Backpropagation Neural Network Implementation for Medical Image Compression. Journal of Applied Mathematics No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-472771
American Medical Association (AMA)
Dimililer, Kamil. Backpropagation Neural Network Implementation for Medical Image Compression. Journal of Applied Mathematics. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-472771
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-472771