Abstract
In order to improve the retrieval efficiency of massive medical images,a new medical image retrieval system was proposed based on distributed Hadoop to solve the low efficiency of medical image retrieval system based on single node.Firstly,the features of medical image were extracted by using Brushlet transform and Local Binary Pattern(LBP) algorithm,and the feature database was stored in the Hadoop Distributed File System(HDFS). Secondly,the Map was used to match the features of retrieval images and medical images in the library,and the matching results of the Map task were collected and sorted by the Reduce function. Finally,the optimum results of medical image retrieval were obtained according to the ordering. The test results show that,compared with other medical image retrieval systems,the proposed system reduces the time of image storage and retrieval,and improves the image retrieval speed.
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