State-of-the-art techniques on medical image retrieval using Hadoop

N. Renukadevi
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引用次数: 1

Abstract

The role of medical imaging in today's system of health care is very prominent and its wide usage as now created databases of images called PACS or Picture Archiving and Communication Systems. Large storage facilities for computers are employed by departments of medical imaging though the PACS method. Images from different modalities like multidimensional and also 2D images as well as multimodality images are now stored. These images can result in more efficient diagnosis, and also better teaching and research. This necessitates the right method to be employed for searching images having the same traits to their region of interest. CBIR or Content-based image retrieval can be taken as a technique for retrieving images which enables a balance between the conventional methods of text based retrieval that uses visual features like colour, shape, texture etc. Medical CBIR is now a field of study that has established itself and has proved to be true when it is applied to multimodality as well as multidimensional medical data. An image retrieval system that is based on content and further on Hadoop, which is a projected solution for big image database that provides safe and effective search methods and also retrieves those images that are similar to the Query image of the database.
使用Hadoop进行医学图像检索的最新技术
医学成像在今天的医疗保健系统中的作用是非常突出的,它的广泛使用是现在创建的图像数据库,称为PACS或图像存档和通信系统。医学影像科室通过PACS方法使用大型计算机存储设备。来自不同模态的图像,如多维和二维图像以及多模态图像现在被存储。这些图像可以导致更有效的诊断,也可以更好的教学和研究。这就需要使用正确的方法来搜索具有与其感兴趣区域相同特征的图像。CBIR或基于内容的图像检索可以被视为一种检索图像的技术,它可以在传统的基于文本的检索方法(使用颜色、形状、纹理等视觉特征)之间取得平衡。医学CBIR现在是一个研究领域,它已经确立了自己的地位,并在应用于多模态和多维医学数据时证明是正确的。一种基于内容并进一步基于Hadoop的图像检索系统,它是一种面向大图像数据库的投影解决方案,提供安全有效的搜索方法,同时也能检索到与数据库查询图像相似的图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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