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101.
对CFG桩质量缺陷的探讨 总被引:2,自引:2,他引:0
根据具体工程的概况及水文地质条件,分析了CFG桩在地下水位出现大面积缩颈现象和复合地基载荷试验达不到设计要求的原因,并介绍了地基补强措施,以满足工程质量的要求。 相似文献
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姜浩 《信息安全与通信保密》2006,(10):49-50
论文详细描述并分析了从RC5到RC6的演化设计过程,在详细研究了RC6性能的同时,指出了应该如何从一个旧的密码设计出好的新密码。最后对RC6和Rijndael作了一些比较,指出各自在性能上的优缺点。 相似文献
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Hui Luo Wei Hao David H Foos Craig W Cornelius 《IEEE transactions on information technology in biomedicine》2006,10(2):302-311
Chest radiography is one of the most widely used techniques in diagnostic imaging. It comprises at least one-third of all diagnostic radiographic procedures in hospitals. However, in the picture archive and communication system, images are often stored with the projection and orientation unknown or mislabeled, which causes inefficiency for radiologists' interpretation. To address this problem, an automatic hanging protocol for chest radiographs is presented. The method targets the most effective region in a chest radiograph, and extracts a set of size-, rotation-, and translation-invariant features from it. Then, a well-trained classifier is used to recognize the projection. The orientation of the radiograph is later identified by locating the neck, heart, and abdomen positions in the radiographs. Initial experiments are performed on the radiographs collected from daily routine chest exams in hospitals and show promising results. Using the presented protocol, 98.2% of all cases could be hung correctly on projection view (without protocol, 62%), and 96.1% had correct orientation (without protocol, 75%). A workflow study on the protocol also demonstrates a significant improvement in efficiency for image display. 相似文献
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Jinman Kim Weidong Cai Dagan Feng Hao Wu 《IEEE transactions on information technology in biomedicine》2006,10(3):598-607
The advances in digital medical imaging and storage in integrated databases are resulting in growing demands for efficient image retrieval and management. Content-based image retrieval (CBIR) refers to the retrieval of images from a database, using the visual features derived from the information in the image, and has become an attractive approach to managing large medical image archives. In conventional CBIR systems for medical images, images are often segmented into regions which are used to derive two-dimensional visual features for region-based queries. Although such approach has the advantage of including only relevant regions in the formulation of a query, medical images that are inherently multidimensional can potentially benefit from the multidimensional feature extraction which could open up new opportunities in visual feature extraction and retrieval. In this study, we present a volume of interest (VOI) based content-based retrieval of four-dimensional (three spatial and one temporal) dynamic PET images. By segmenting the images into VOIs consisting of functionally similar voxels (e.g., a tumor structure), multidimensional visual and functional features were extracted and used as region-based query features. A prototype VOI-based functional image retrieval system (VOI-FIRS) has been designed to demonstrate the proposed multidimensional feature extraction and retrieval. Experimental results show that the proposed system allows for the retrieval of related images that constitute similar visual and functional VOI features, and can find potential applications in medical data management, such as to aid in education, diagnosis, and statistical analysis. 相似文献
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