Telemedicine Medical Image Compression based on ROI (A Case Study of Spine Medical Images)

Abstract

In recent years, telemedical need arose, as a result of the increasing numbers of patients significantly, where using image compression is one of the most important techniques in the field processing research field, as well as in multiple applications such as medicine, reconnaissance, aerial surveillance, and space. Image compression necessary to reduce transport costs due to rising transport prices and distances In this method, we divide the original image into two separate sub-images called ROI and non-ROI. Region of interest (ROI) is the decisive area in a medical image, which is very important. This area may indicate a disease and must result in a right diagnosis. We use the spread spectrum-embedding algorithm to embed a binary mark into DCT transform of non-ROI part of an image.  In this search review the compression of the medical images and encoded and then decoder with no distort medical images was taken for sections of the spine for sick people.  Used in the field of telemedicine, Medical images encoded works with LSK through use WT (wavelet transform), During the user interaction (encryption) obtained of the ROI regions that lead us to get high compression ratio.The method used in this technology decompress on the block and like-minded countries on the basis of the value stored, note that the time of implementation of this method is low when compared with other methods.

Keywords: Telemedicine, Medical Image Compressing, ROI, fractal image compression, LSK.