A Multimodal Search Engine for Medical Imaging Studies


The use of digital medical imaging systems in healthcare institutions has increased significantly, and the large amounts of data in these systems have led to the conception of powerful support tools: recent studies on content-based image retrieval (CBIR) and multimodal information retrieval in the field hold great potential in decision support, as well as for addressing multiple challenges in healthcare systems, such as computer-aided diagnosis (CAD). However, the subject is still under heavy research, and very few solutions have become part of Picture Archiving and Communication Systems (PACS) in hospitals and clinics. This paper proposes an extensible platform for multimodal medical image retrieval, integrated in an open-source PACS software with profile-based CBIR capabilities. In this article, we detail a technical approach to the problem by describing its main architecture and each sub-component, as well as the available web interfaces and the multimodal query techniques applied. Finally, we assess our implementation of the engine with computational performance benchmarks.

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Correspondence to Eduardo Pinho.

Appendix: Multimodal Query Schema

Appendix: Multimodal Query Schema


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Pinho, E., Godinho, T., Valente, F. et al. A Multimodal Search Engine for Medical Imaging Studies. J Digit Imaging 30, 39–48 (2017). https://doi.org/10.1007/s10278-016-9903-z

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  • Content-based image retrieval
  • Computer systems
  • Graphical user interface (GUI)
  • Information storage and retrieval
  • PACS
  • Reproducibility of results
  • Software design
  • Multimodal information retrieval
  • Query fusion
  • Web services