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Efficient and robust large medical image retrieval in mobile cloud computing environment

机译:移动云计算环境中高效健壮的大型医学图像检索

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This paper presents an efficient and robust content-based large medical image retrieval method in mobile Cloud computing environment, called the MIRC. The whole query process of the MIRC is composed of three steps. First, when a clinical user submits a query image Iq, a parallel image set reduction process is conducted at a master node. Then the candidate images are transferred to the slave nodes for a refinement process to obtain the answer set. The answer set is finally transferred to the query node. The proposed method including an priority-based robust image block transmission scheme is specifically designed for solving the instability and the heterogeneity of the mobile cloud environment, and an indexsupport image set reduction algorithm is introduced for reducing the data transfer cost involved. We also propose a content-aware and bandwidth-conscious multi-resolutionbased image data replica selection method and a correlated data caching algorithm to further improve the query performance. The experimental results show that the performance of our approach is both efficient and effective, minimizing the response time by decreasing the network transfer cost while increasing the parallelism of I/O and CPU.
机译:本文提出了一种在移动云计算环境中有效且强大的基于内容的大型医学图像检索方法,称为MIRC。 MIRC的整个查询过程包括三个步骤。首先,当临床用户提交查询图像Iq时,在主节点处进行并行图像集缩减处理。然后将候选图像传输到从节点进行细化处理以获得答案集。答案集最终被传送到查询节点。提出的包括基于优先级的鲁棒图像块传输方案的方法是专门为解决移动云环境的不稳定性和异构性而设计的,并引入了索引支持图像集约简算法来减少所涉及的数据传输成本。我们还提出了一种基于内容感知和带宽意识的多分辨率图像数据副本选择方法以及相关数据缓存算法,以进一步提高查询性能。实验结果表明,我们的方法的性能既高效又有效,它通过降低网络传输成本,同时增加了I / O和CPU的并行性,最大限度地缩短了响应时间。

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