Edge Preserving Image Compressor (EPIC) in Medical Image Using Dynamic Associative Neural Networks

Abstract

Telemedicine is the method which uses digital technology for practitioners to medical diagnosis fast treatment of patient’s and use of knowledge in research work. But at the same time it increases the challenge to store, transmission high resolution and big size DICOM images. To reduce the size it should be compressed before transmission and store over the network and use the method to maintain the image quality in restoration of image because the each and every bit information can change the diagnosis method. To achieve this compression number of amalgamated technology developed in recent years. Artificial Neural Network techniques are to accomplish high quality image restoration of medical image. To achieve execution augmentation with respect to compression ratio and deciphered image quality is developed using Edge Preserving Image Compressor with Dynamic Associative of Back propagation networks for image compression. Artificial neural network compression techniques rooted on Dynamic Associative Neural Networks (DANN), to achieve high compression quality restoration in an Edge Preserving Image Compressor well-suited to parallel implementations.