Medical image transmission through web using secured network

Abstract

With the rapid development of communications technology, various methods of medical image transmission are investigated. Transmission of medical images over a distance using telecommunication means provides expert based medical care to any place that requires health care. In this research, medical image transmission through web is implemented in which the medical images are transmitted in a client server architecture in a compressed form using Direct Cosine Transformation (DCT) method. The server compresses the image file using DCT technique. In the client side, the decompressed image is obtained using inverse DCT. After an elaborate survey on existing systems, it seems that there are possibilities for improvement in processing speed for image compression using Field Programmable Gate Array (FPGA) as coprocessor with Digital Signal Processor (DSP). To find the optimum transformation technique suitable for image transmission with less storage space and low band width requirements, Computed tomography (CT) images are compressed using Joint Photographic Expert Group (JPEG) and Discrete wavelet Transformation (DWT) method. In the Security of the Medical image during transmission from physician to another physician, there is a possibility of leakage of medical information due to intruders and will lead to altering of medical image details. It also changes the line of treatment and diagnosis. Hence to provide security in the network, the use of Genetic Algorithm newline(GA) based intrusion detection system (IDS) has been explored and it also detects the new anomalies generated time to time. GA is executed using crossover and mutation by selecting the best rule and these rules are stored in the data base. Identification of anomalies is clearly defined by set of rules with various attributes. To achieve this, GA based IDS has been implemented and tested with specific simulated anomalies in a local network and new rules are created due to time evolving nature of GA to detect the new anomalies. newline newline newline