Adaptive Medical Image Compression Algorithm Based On Evolutionary Algorithm Is Studied

With the development of image processing and computer technology, the realization of high quality medical image has greatly improved the diagnostic accuracy and predictability of clinical disease and changed the low-efficiency mode of traditional medical diagnosis. Quality and information of medical image which acquired by high precision image equipment are more and more high, consequently, the storage and transmission of these images requirements big space and wide bandwidth which has brought great pressure to hospital. The size of the image data will affect the effective of preservation and transmission in hospital’s picture archiving and communication system and remote medical experts consultation system. Data compression is the main traditional technology of solving data storage problem, the research of an effective method which can reduce the amount of medical image data in storage and transmission caused many medical experts and scholars’wide attention.Based on the analysis of the existing image compression technology, author has made in-depth studies and experiments according to the requirements and features of medical image compression and proposed the medical image compression method based on evolutionary algorithm, moreover, gave the concrete realization method and experiment results. The main work and innovations as following:1Making In-depth studies in basic principles and research status of image compression. The author has analyzed and compared the conventional image compression algorithms, and then gave the analysis and summary of current algorithm of medical image compression and research status based on the analysis of lossless and loss compression combined with the respectively pros and cons characteristics of medical images.2Evolutionary algorithm is introduced to self-adapting medical image compression technology. In view of loss compression’s high compression ratio but low fidelity and lossless compression’s high fidelity but low compression ratio, the evolutionary algorithm is introduced to the medical image compression technology by constructing compression effect fitness function, using evolutionary algorithm to look for global optimization value and adjusting compression effect through the evolutionary operation considered the various factors of image compression quality evaluation standards. The experiment showed that the compression effect of different medical images is both high-fidelity and maximum compression ratio.3Improving the medical image compression speed and quality by means of improved evolutionary algorithm operators. Considering the traditional evolutionary algorithm is easy to fall into local optimum and convergence insufficiency, the adaptive evolutionary algorithm is used to adjust the evolution operation factor for guaranteeing the optimization search fast convergence and prematurity. The results show that, improved evolutionary algorithm not only guaranteed the global optimization but also shortened the searching time effectively, improved the compression rate and quality.4The mix medical image compression method combined with loss-compression and the lossless-compression technology is proposed. Medical image compression’s high fidelity requirements is for the sake of the integrity of the information, and the site of lesion is very small percentage in the whole image. Therefore, it can effectively improve the compression efficiency if the lesion site only can be compressed lossless in medical image compression process. This paper combines lossless and loss compression methods, the lesion site what is extracted by image segmentation and extraction of region of interest was high fidelity compression by lossless compression method and other ancillary parts was high ratio compression by loss compression method, the Mixed compression method not only realizes the effective compression effect but also ensure that contains important pathological information site fidelity.