Fractal image coding for emission tomographic image compression

With the increasing use of teleradiology systems, large amount of data is acquired and transmitted, thus raising the issue of medical image compression. The goal of image compression is to represent an image with as few number of bits as possible while preserving the quality required for the given application. Standard lossless compression schemes can only yield compression ratios of about 2:1 that is insufficient to compress volumetric tomographic image data. Common standards available in industry for lossy image compression are usually used in non-medical applications and their application to medical image compression is still under investigation. Fractal image coding is a new compression technique that has received much attention recently. This study investigates the feasibility of applying fractal image coding approach to nuclear medicine image compression. A quadtree-based partition scheme was used in the encoding phase to partition an image frame into small irregular segments that after decoding process, yield an approximate image to the original. Our preliminary results show that compression ratios higher than 10:1 can be achieved in clinical images. It was also found that there is no diagnostic loss in the parametric images computed from the reconstructed images as compared to those obtained from the original raw data. We conclude that fractal image coding could be used to compress tomographic images and it may be useful in telemedicine.