International Journal of Computer Theory and Engineering

Abstract

Telemedicine characterized by transmission of medical data and images between users is one of the emerging fields in medicine. Huge bandwidth is necessary for transmitting medical images over the internet. Resolution factor and number of images per diagnosis makes even the size of the images that belongs to a single patient to be very large in size. So there is an immense need for efficient compression techniques for use in compressing these medical images. Each of the regions that are considered to be more important than others in medical images is termed as a Region of Interest (ROI) e.g. tumor region of the brain MRI. Thus, the regions of interest can be coded with high spatial resolution than the background while transmitting the images. By this, ROI of high compression rate and high quality can be obtained. This paper reviews the application of ROI coding in the field of telemedicine. Wavelet transform with lifting is used to perform image coding based on Set Partitioning in Hierarchical Trees (SPIHT). ROI coding with high spatial resolution than the background is accomplished using tiling method. High compression ratio is achieved by obtaining the ROI through user interaction and coding with the user given resolution. The experimental result shows that the application of ROI coding achieves high compression rate and quality ROI by using wavelet with lifting and tiling method.