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Journal of Digital Imaging

, Volume 26, Issue 6, pp 1025–1039 | Cite as

Content-Based Medical Image Retrieval: A Survey of Applications to Multidimensional and Multimodality Data

  • Ashnil KumarEmail author
  • Jinman Kim
  • Weidong Cai
  • Michael Fulham
  • Dagan Feng
Article

Abstract

Medical imaging is fundamental to modern healthcare, and its widespread use has resulted in the creation of image databases, as well as picture archiving and communication systems. These repositories now contain images from a diverse range of modalities, multidimensional (three-dimensional or time-varying) images, as well as co-aligned multimodality images. These image collections offer the opportunity for evidence-based diagnosis, teaching, and research; for these applications, there is a requirement for appropriate methods to search the collections for images that have characteristics similar to the case(s) of interest. Content-based image retrieval (CBIR) is an image search technique that complements the conventional text-based retrieval of images by using visual features, such as color, texture, and shape, as search criteria. Medical CBIR is an established field of study that is beginning to realize promise when applied to multidimensional and multimodality medical data. In this paper, we present a review of state-of-the-art medical CBIR approaches in five main categories: two-dimensional image retrieval, retrieval of images with three or more dimensions, the use of nonimage data to enhance the retrieval, multimodality image retrieval, and retrieval from diverse datasets. We use these categories as a framework for discussing the state of the art, focusing on the characteristics and modalities of the information used during medical image retrieval.

Keywords

Content-based image retrieval Medical images Multimodality data Multidimensional data Review 

Notes

Acknowledgments

We are grateful to our collaborators at the Royal Prince Alfred Hospital, Sydney, Australia for their direct and indirect contributions to this work. This work was supported in part by ARC grants.

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Copyright information

© Society for Imaging Informatics in Medicine 2013

Authors and Affiliations

  • Ashnil Kumar
    • 1
    Email author
  • Jinman Kim
    • 1
  • Weidong Cai
    • 1
  • Michael Fulham
    • 1
    • 2
    • 3
  • Dagan Feng
    • 1
    • 4
  1. 1.Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information TechnologiesUniversity of SydneySydneyAustralia
  2. 2.Department of Molecular ImagingRoyal Prince Alfred HospitalSydneyAustralia
  3. 3.Sydney Medical SchoolUniversity of SydneySydneyAustralia
  4. 4.Med-X Research InstituteShanghai Jiao Tong UniversityShanghaiChina

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