High quality model for compression of medical images in telemedicine

摘要

Generally lossless compression should be used for ROI (Region of Interest) and lossy compression should be used for ROB (Region of Background) with a lower quality. In existing system, Region of Interest (ROI) is selected manually, but ROI is selected automatically in the proposed method, pre-processing is done to improve the visual quality of the image. Segmentation is carried out accurately and efficiently using region growing followed by morphological processing method. The features are extracted and classification is done in medical image using Fuzzy logic. ROB part of an image is compressed using SPIHT (Set Partition In Hierarchical Tree) algorithm in near lossless manner. Finally the ROI is superimposed in compressed Non ROI (ROB) image. This method improves the compression ratio and increase the PSNR value compared to existing method. The proposed method is used for implementations of teleradiology and digital picture archiving and communications (PACS) systems practically.