A Novel Medical Image Compression Technique using 3d Wavelet

Medical Image Compression in 3D is one of the growing research fields in biomedical applications. Three dimensional (3D) medical images are increasingly used in many clinical and research applications. The problem is whether to compress the image slices in lossy or lossless compression schemes. Propose a feature based classification frame work in order to categorize the Slices as normal or abnormal. After categorization normal slices are subjected to lossy compression and abnormal slices are subjected to lossless compression. The Gray Level Co-occurrence Matrix (GLCM) is constructed to extract the spatial features from the selected image slices. The feature vectors obtained from the GLCM are given as input to the SVM classifier for classification. Performance of SVM classification is validated and prone the categorized result to the appropriate Compression schemes. Compression will be experimentally validated by calculating compression ratio.