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Content-based retrieval in picture archiving and communication systems

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Abstract

A Content-Based Retrieval Architecture (COBRA) for picture archiving and communication systems (PACS) is introduced. COBRA improves the diagnosis, research, and training capabilities of PACS systems by adding retrieval by content features to those systems. COBRA is an open architecture based on widely used health care and technology standards. In addition to regular PACS components, COBRA includes additional components to handle representation, storage, and content-based similarity retrieval. Within COBRA, an anatomy classification algorithm is introduced to automatically classify PACS studies based on their anatomy. Such a classification allows the use of different segmentation and image-processing algorithms for different anatomies. COBRA uses primitive retrieval criteria such as color, texture, shape, and more complex criteria including object-based spatial relations and regions of interest. A prototype content-based retrieval system for MR brain images was developed to illustrate the concepts introduced in COBRA.

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Authors and Affiliations

  1. Department of Computer Science, University of North Carolina, Charlotte, NC

    Essam A. El-Kwae, Haifeng Xu & Mansur R. Kabuka PhD

  2. Department of Radiology, Center for Medical Imaging and Medical Informatics, University of Miami, Miami, FL

    Essam A. El-Kwae, Haifeng Xu & Mansur R. Kabuka PhD

  3. Department of Electrical and Computer Engineering, Center for Medical Imaging and Medical Informatics, University of Miami, 1251 Memorial Dr, MCA Rm 406, 33146, Miami, FL

    Essam A. El-Kwae, Haifeng Xu & Mansur R. Kabuka PhD

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  1. Essam A. El-Kwae
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  3. Mansur R. Kabuka PhD
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El-Kwae, E.A., Xu, H. & Kabuka, M.R. Content-based retrieval in picture archiving and communication systems. J Digit Imaging 13, 70–81 (2000). https://doi.org/10.1007/BF03168371

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