Medical Image Retrieval Technology Based On Multiple-inverted File

With the rapid development of medical diagnoses and multimedia information technology,The data of medical image quick increase,How to realize effectiveness of medical image retrieval is a important investigation problem.The technology of high-dimensional index is a science of improving the retrieval effectiveness of high-dimensional database by establishment of index structurc.As an important part of high dimensional database, image database's retrieval ability relies on the support of high-dimensional index technique.Existing high-dimensional index techniques are compared and analyzed. By systematically analyzing of relevant algorithms, high-dimensional index techniques are investigated from theory,algorithm and implementation aspects, and a novel method of index is presented. In additional, a prototype retrieval system of medical image database is designed and implemented based on this novel method. The main work is listed here:1,By study high-dimensional data space searching, high-dimensional data and its index technique are particularly analyzed. The relevant aspects of high-dimensional data query are discussed. The basic idea, structure and algorithms of high-dimensional index are concluded.2,Indexing idea,structure and applicability are compared between metric access method (MAM) and spatial access method(SAM). The similarity and difference of those two methods are summarized. we find difficulty of tree form index structure with the dimension increase. This retrieval effectiveness of index structure will descend rapidly , 'dimension curse'. To overcome the prominent'dimension curse'actuality,we deeply study fields of image database index technique,the researches in this paper have much important theoretical and practical significance.3,A new deep first pruning algorithm Based on Multi-inverted table are proposed. On the basis of inverted index structure, this method, called as Multi-inverted index, makes use of a dynamic inserting algorithm for building index and exploits an ameliorated pruning algorithm which can optimize its structure. Multi-inverted index improves nodes utility of index structure, decreases the quantity I/O of disk and has a prominent advantage that it can be applied to high or hyper-dimensional data retrieval which is proved by experiment.4,On the basis of Multi-inverted index a retrieval system of medical image database is designed and implemented. According to the characteristic of medical image information, this system takes use of the method of annular segmentation to extract regional colour moments as features and applies Multi-inverted index method to index and organize of features database. Extracting feature is simply and the effect of feature index is obvious in this prototype system that improves performance of image retrieval effectively. High-dimensional index is novelty and foreground aspect, The study of this field is weakly. This paper discuss and study several question of relevant, many significance work of High-dimensional index, such as application of index compression. Require continue to study.