Segmentation and compression of medical image using MSPIHT in telemedicine application

Healthcare delivery systems and Telemedical applications will undergo a dramatic change due to the developments in technologies, mobile computing, medical sensors and communication techniques. Medical Images taken as X-ray, Positron Emission Tomography (PET), Magnetic Resonance Imaging (MRI), Ultra Sound and Computed Axial Tomography (CAT) will have medical information either in multi resolution or multidimensional form, this creates large amount of data. Due to this storage of data is become more complex. So compression is needed the one in image processing. Anyhow compression of medical data will leads to loss of information. In order to reduce this complexity, as well as preserve the medical data to be lossless for diagnostics purpose, this paper propose techniques Region growing and Modified Set Partition In Hierarchical Tree (MSPIHT) will enhance the performance of lossless compression and also enhance the Peak Signal to Noise Ratio (PSNR) and Compression Ratio (CR) than the SPIHT coding method.