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Geographically Distributed Complementary Content-Based Image Retrieval Systems for Biomedical Image Informatics

机译:基于地理分布的基于互补内容的生物医学图像信息的图像检索系统

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There is a significant increase in the use of medical images in clinical medicine, disease research, and education. While the literature lists several successful systems for content-based image retrieval and image management methods, they have been unable to make significant inroads in routine medical informatics. This can be attributed to the following: (i) the challenging nature of medical images, (ii) need for specialized methods specific to each image type and detail, (Hi) lack of advances in image indexing methods, and (iv) lack of a uniform data and resource exchange framework between complementary systems. Most systems tend to focus on varying degrees of the first two items, making them very versatile in a small sampling of the variety of medical images but unable to share their strengths. This paper proposes to overcome these shortcomings by defining a data and resource exchange framework using open standards and software to develop geographically distributed toolkits. As proof-of-concept, we describe the coupling of two complementary geographically separated systems: the IRMA system at Aachen University of Technology in Germany, and the SPIRS system at the U. S. National Library of Medicine in the United States of America.
机译:在临床医学,疾病研究和教育中使用医学图像有显着增加。虽然文献列出了几个用于基于内容的图像检索和图像管理方法的成功系统,但它们无法在日常医疗信息中进行重大进展。这可以归因于以下内容:(i)医学图像的具有挑战性,(ii)需要针对每个图像类型和细节的专用方法,(HI)缺乏图像索引方法,(iv)缺乏互补系统之间的统一数据和资源交换框架。大多数系统倾向于专注于前两个项目的不同程度,使它们在各种医学图像的小型采样中非常通用,但无法分享他们的优势。本文通过使用开放标准和软件定义数据和资源交换框架来开发地理分布式工具包来克服这些缺点。作为概念验证,我们描述了两个互补地理上分离系统的耦合:德国Aachen工业大学的IRMA系统,以及美国美国美国医学图书馆的Spirs系统。

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