Research Of Compression Method For Medical Image

Recently, medical image compression technology is one of the important subjects within medical image database research field and worked over throughout the world. The main purpose of medical image compression is to express more clinic information with less data, which can reduce storage and transmission time. Due to limitations of storage and bandwidth, medical images must be compressed in medical image database system.The investigating statuses in quo and developments about medical image compression in domestic and foreign fields are reviewed and summarized. Aiming at practical demands of medical image database, this paper discusses the purpose, significance and researching status of medical image compression. Lossless and lossy compression methods for medical image are analyzed and improved measures are presented to overcome all demerits. In order to resolve the conflict between lossless and lossy compression methods, a new ROI-based medical image compression scheme is put forward according to the features and special application requirements of medial image.In this paper, compression techniques for medical image are investigated from theory , algorithm and implementation aspects. Study fruits related to some techniques in medical image compression are introduced completely and its main contents include:1. In this work, lossless medical image compression methods are compared. Strongpoints and shortcomings of each method are particularly analyzed. Applying each method to lots of real medical images, we find lossless medical image compression methods.2. Transform-based medical image compression is researched mostly. One of the major drawbacks of the block-based DCT medical image compression is that there are many visible artifacts at block boundaries in the uncompressed image. In this paper, we make a deep research on the reason that result in visible artifacts. We also propose an adaptive approach that performs blockness reduction in the DCT domains to reduce the block-to -block discontinuities.3. In the research of medical image compression based on discrete wavelet transform, some issues are discussed, involving in wavelet selecting, deciding decomposed level and converting coefficients in transformed domain. Encoding methods for DWT-based medical image compression, such as Embedded Zerotree Wavelet coder, Set Partitioning In Hierarchical Trees coder, Set Partitioned Embedded Block coder and Compression with Reversible Embedded Wavelets coder are investigated across-the round.4. On the basis of the clinic diagnostic requirements, medical image compression with lossless regions of interest is studied, which makes full use of strongpoints of lossless and lossy medical image compression methods. We also offer an effective ROI-based medical image compression method, which is capable of compressing CT images. In this method, a medical image is segmented into region of interest and residual region, then, lossless compression and lossy compression are implemented at the interested region and residual region respectively...