Comparative Study of Wavelet Families for Biomedical Image Compression

Abstract

A lot of hospitals handle their medical image data with computers. The use of computers and a network makes it possible to distribute the image data among the staff efficiently. As the health care is computerized new techniques and applications are developed, among them are the MR and CT techniques. MR and CT produce sequence of images (image stacks) each alng the cross-section of an object. The amount of data produced by these techniques is vast and this might be a problem when sending the data over a network. To overcome this problem image compression has been introduced in the field of medical. Medical image compression plays a key role as hospitals, move towards film- less imaging and go completely digital compression. Image compression will allow Picture Archiving and Communication Systems (PACS) to reduce the file sizes on their storage requirements while maintaining relevant diagnostic information. There have been numerous compression research studies, examining the use of compression as applied to medical images. The techniques can be categorized as, focusing on just a lossless compression method, on just a lossy compression method, or focusing on both. Most have focused on lossless algorithms since the medical community has been reluctant to adopt lossy techniques owing to the legal and regulatory issues that are raised, but this