Research And Implementation Of Wideband High Resolution Frequency Synthesizer

Nowadays,medical imaging systems have become an indispensable accessory tool for clinical and medical research.With the rapid development of medical imaging technology,computer-aided diagnostic technology in medical research and clinical experiments has been hugely prompted towards high demand and rapid development because medical image processing forms the basis of computer-aided diagnostic techniques.Therefore,medical image processing technology remains one of the hotspots in multidisciplinary research in the field of computer science and medicine.The high increase in the number of the aging population battling with the Alzheimer's disease makes it an increasing burden for the medical community.In solving this problem,it can take full advantage of modern computer capability such as high processing speed,low cost and high efficiency.As such,this thesis focus on the basis of computer-aided diagnosis system of Alzheimer's disease technology research.This involves research on original brain medical image pretreatment and then the method of brain tissue extraction fully illustrated.Finally,the thesis focus on analysis of brain tissue segmentation and brain volume measurement technology.As such,the main research results of the thesis include the following:(1)Using modern image denoising technology to create a set of denoising process for brain medical image.(2)By analyzing the characteristics of brain medical images and the structure of the human brain,and then use of multiple threshold segmentation algorithm to extraction of brain tissue.(3)By analyzing the shortcomings of two classical clustering algorithms;Gaussian mixture model and the k-means algorithms in segmenting the brain tissue.Also fusing both algorithms to achieve a more improved GKA algorithm for brain image segmentation its tissues.(4)Two different methods of measuring the brain tissue area and volume are proposed in this thesis,then a comprehensive experimental result comparison of the two schemes are adequately discussed.After engaging tests using Magnetic resonance images from clinical procedures,it can be concluded that the medical image denoising process and brain tissue extraction algorithm obtained ideal and accurate experimental results.In the brain tissue segmentation,the results of the GKA method provided better results compared to the traditional Gaussian mixture model and k-means clustering algorithm in each index.In terms of the measurement of brain tissue area,because the two methods proposed in this thesis are based on different definitions of brain tissue area,the results of the two methods are different but both of the results have certain distinguishable clinical reference value.