An Optimal Mammogram Image Compression based on Neural Network Classifier and the Newton Algorithm
Journal Title: International Research Journal of Applied and Basic Sciences - Year 2014, Vol 8, Issue 12
Abstract
In Telemedicine, digital utilization for medical diagnosis increase the storage resource requirement for archive the images and uncompressed data requires considerable storage capacity and transmission bandwidth. Successful implementations of artificial intelligent algorithms have now become well established and one important of AI is neural network involvement in this category. This study is an application of mammography images compression of patients using neural networks and the Newton algorithm, which allows carrying out both compression of the mammograms with a fixed ratio of 8:1 and a loss of 3%. The outcomes of this work are more than satisfying the exactness of the mammograms compressed with the proposed hybrid compression method meets the requirements imposed on these images and the neural networks magnification outperforms other magnification algorithms.
Authors and Affiliations
Bahare Nosrati Nia*| Department of Electrical and Computer Engineering, Sabzevar, Iran, email: Bahare.nosratinia@gmail.com, Javad Haddadnia| Department of Electrical and Computer Engineering, Sabzevar, Iran
Keywords
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