【作者】 吴微；

【导师】 朱玉全；

【作者基本信息】 江苏大学 ， 计算机应用技术， 2008， 硕士

【摘要】 随着电子计算机断层摄影、核磁共振成像技术等医学成像技术的产生和发展,人们获得了越来越多可供临床诊断的医学图像,如何有效地利用计算机技术对其进行分类已成为国内外许多学者研究的一个热点问题。另外,在现实环境中,许多医院的医学图像数据是分散存放的,它们之间除了通过网络传递信息外,其它资源全部独立。因此,研究并提出适合于分布式医学图像的分类方法具有较高的学术价值和广泛的应用前景。论文讨论了分布式医学图像分类挖掘的背景、意义和国内外研究状况。针对医学图像存放的特点及分布式医学图像分类挖掘的实际应用要求,提出了解决分布式医学图像分类的方法。对现有决策树算法存在的问题,提出基于SLIQ的改进算法DMI_SLIQ,较好地解决了分布式分类挖掘问题,初步建立了基于SLIQ的分布式医学图像分类框架。论文从理论、算法和应用三个方面对分布式医学图像分类方法进行了研究,主要工作包括:1、本文将分类技术与数字图像处理技术有机结合,研究了分布式医学图像的主要分类方法,并给出了本文实验所用到的医学图像特征。2、针对SLIQ算法的缺点,提出了DMI_SLIQ算法,从而解决了SLIQ算法搜索空间巨大,耗时多等问题。3、设计并实现了一个分布式协调器算法,用来初始化和管理Agent的分类活动,管理和控制事务的运行。4、针对医学图像分布式存放的特点,提出了一个适用于分布式医学图像分类的框架。该框架包括:表示层、处理层、采掘层。5、实现了分布式医学图像分类实验系统—DMIDM,在系统中实现了本文提出的分布式协调器任务调度算法、全局模型规则生成算法。更多还原

【Abstract】 With the development of computer tomography, magnetic resonance imaging technology, and other medical imaging technology, People has gained the more and more diagnosis of medical image , how effective use of computer technology to classify so many scholars has become a hot issue both at home and abroad. In reality, medical image data are scattered store in many hospitals. They transfer the information outside between them except passing a network, other all independences of resource. Therefore, the study and propose appropriate to the classification of medical images distributed method has a fairly high academic value and broad application prospects.The paper take the medicine image data as the research object, from the theory, the algorithm and applied three aspects to conduct there search to the distributional medicine picture classification method. In view of the existing policy-making tree algorithm existence question, we proposed improvement algorithm DMI_SLIQ based on SLIQ, DMI_SLIQ has solved the distributional classified excavation problem. This paper has established distributional medicine image classification frame based on the SLIQ.The paper from the theory, the algorithm and applied three aspects to conduct the research to the distributional medicine picture classification method, the main work included 1. This article classifies technical and the digital medical image processing technology, and has studied the main method about the distributional medicine picture classified, and has produced the medicine picture characteristic which this article tests uses.2. In view of the decision tree algorithm SLIQ shortcoming, this paper improved and proposed the DMI_SLIQ algorithm. Thus solves the SLIQ algorithm search space greatly, consumes when are to many and so on the question, and compared with algorithm performance, through analysis experiment result.3. In view of the medicine picture distributional depositing characteristic, distributional medicine image classification theory frame is proposed suitable for the issue. This frame divides into three parts, we produces each detailed design thought and the principle of work.4. This paper has realized distributional medicine image classification experiment system DMIDM, and realized the distributional synchronizer duty dispatch algorithm, the overall situation model rule production algorithm in the system which this article proposed. The framework includes: that layer, layer handling, and mining layer.更多还原