Adaptive Edge Enhancement For Ultrasound Imaging

With the rapid development of the technologies such as electronics, computer technology and materials science, the medical imaging technology has made great progress. As the branch of the medical imaging technology, the ultrasonic medicine is the advanced comprehensive subject and develops very quickly. As the important application of the ultrasonic medicine, ultrasonic diagnostic technology has performed great function by its unique features(safety,quickness and real time) and has been widely used in the clinical medicine .Recently, ultrasonic technology has provided the rich and exact information to medicine diagnostic has played a positive role in the morbid no wound exactitude diagnostic . The image edges reflect the most valuable information of the image and are the most important and classic research subject in the image processing and computer vision. For the medical images, the edges are always necessary to determine the focus size, the viscera situation and blood corpuscle fluxion state etc. But with the effect of many factors, the edge of medical images is often not clear , so the diagnosis and medical treatment will be affected, So, the methods of enhancement and and extraction about the image edge and profile feature are continuously the research hotness in the technologies of medical image handling and analysis.In order to be convenient to the medical imaging workers, this thesis firstly introduces the various classic algorithms about the image edge enhancement and analyzes the advantages and disadvantages of all the image edge enhancement methods. Compared to the above classic edge enhancement operators, the new method—Adaptive Edge Enhancement for Ultrasound Imaging—has been put forward. This algorithm makes use of spatial grey level dependence matrices for texture analysis—spatial grey level co-occurrence matrix of 2-D statistics figure out texture of nine parameter. But in the actual application, spatial grey level co-occurrence matrix of 2-D statistics arithmetic has its disadvantages, such as complex calculation, feature fetching in the long time., So we have adopted " sum and difference histograms" of arithmetic that M.Unser has brought forward to replace spatial grey level co-occurrence matrix of 2-D statistics arithmetic . With this simple algorithm, we can easily calculate spatial grey level co-occurrence matrix of 2-D statistics of nine parameter. Through a great lot of practice, now we have approximately computed nine factors , only three of which are useful to our edge enhancement: mean,variance and correnlation . In the thesis, we have carried out the algorithm of various classic edge enhancement operators and Adaptive Edge Enhancement for Ultrasound Imaging method by language C From the results comparison of the above algorithms, our algorithm is not only simple but also much effective, and it is the very useful method in the edge enhancement。...