文章基本信息

标题：Massive Medical Images Retrieval System Based on Hadoop
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作者：YAO, Qing-An ; ZHENG, Hong ; XU, Zhong-Yu 等
期刊名称：Journal of Multimedia
印刷版ISSN：1796-2048
出版年度：2014
卷号：9
期号：2
页码：216-222
DOI：10.4304/jmm.9.2.216-222
语种：English
出版社：Academy Publisher
摘要：In order to improve the efficiency of massive medical images retrieval, against the defects of the single-node medical image retrieval system, a massive medical images retrieval system based on Hadoop is put forward. Brushlet transform and Local binary patterns algorithm are introduced firstly to extract characteristics of the medical example image, and store the image feature library in the HDFS. Then using the Map to match the example image features with the features in the feature library, while the Reduce to receive the calculation results of each Map task and ranking the results according to the size of the similarity. At the end, find the optimal retrieval results of the medical images according to the ranking results. The experimental results show that compared with other medical image retrieval systems, the Hadoop based medical image retrieval system can reduce the time of image storage and retrieval, and improve the image retrieval speed.
关键词：Medical Image Retrieval;Feature Library;Brushlet Transform;Local Binary Patterns;Distributed System