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Medical Image Retrieval System in Grid Using Hadoop Framework

机译:使用Hadoop框架的网格医学图像检索系统

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In the last few years there has been tremendous increase in the storage and processing of data, with significant speed and storage space requirements. Medical image storage and retrieval is one such application which requires huge storage space and not easily solved by computers. The researchers who work in the area of medical image processing deal with a high degree of storage and retrieval of medical images. Digitizing medical images and computer based image retrieval replaces the use of hard copies and provides efficient remote access. The proposed grid architecture implemented in this work uses Apache Hadoop framework. Hadoop is an open source grid architecture, complies with various image formats and can be established among various hospitals to store, share and retrieve images. Various performance metrics such as reliability, accuracy, interoperability, confidentiality and security are improved as with the use of Hadoop. The user authentication and patient confidentiality is also achieved. In this work, texture based Content Based Image Retrieval (CBIR) algorithm is used for efficient image retrieval. The performance of the proposed image retrieval system using Hadoop is tested with three current operative nodes. Experimental results obtained show that the retrieval time of the proposed system, Hadoop-CBIR, is considerably less with large number of images in the database.
机译:在过去的几年中,数据的存储和处理有了巨大的增长,对速度和存储空间的要求也很高。医学图像的存储和检索就是这样一种应用,它需要巨大的存储空间,并且不易被计算机解决。在医学图像处理领域工作的研究人员处理医学图像的高度存储和检索。医学图像数字化和基于计算机的图像检索取代了硬拷贝的使用,并提供了有效的远程访问。在这项工作中实现的建议的网格体系结构使用Apache Hadoop框架。 Hadoop是一种开源网格体系结构,符合各种图像格式,可以在各种医院之间建立以存储,共享和检索图像。随着Hadoop的使用,各种性能指标(如可靠性,准确性,互操作性,机密性和安全性)得到了改善。还可以实现用户身份验证和患者机密性。在这项工作中,基于纹理的基于内容的图像检索(CBIR)算法用于有效的图像检索。所提出的使用Hadoop的图像检索系统的性能已通过三个当前操作节点进行了测试。获得的实验结果表明,在数据库中有大量图像的情况下,所提出系统Hadoop-CBIR的检索时间大大减少。

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