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Mammographic Image Database (MIDB) and Associated Web-Enabled Software for Research

  • Mark D. Halling-Brown
  • Pádraig T. Looney
  • Mishal N. Patel
  • Lucy M. Warren
  • Alistair Mackenzie
  • Kenneth C. Young
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8539)

Summary

Current efforts relating to the uptake, evaluation and research into digital medical imaging require the large-scale collection of images (both unprocessed and processed) and data. This demand has led us to design and implement a flexible mammographic image repository, which prospectively collects images and data from multiple screening sites throughout the UK. The MIDB has been designed and created to provide a centralised, fully annotated dataset for research purposes. One of the most important features is the inclusion of unprocessed images. In addition to the images and data, systems have been created to allow expert radiologists to annotate the images with interesting clinical features and provide descriptors of these features. MedXViewer (Medical eXtensible Viewer) is an application we have designed to allow workstation-independent, PACS-less viewing and interaction with anonymised medical images (e.g. for observer studies). With these integrated tools, the MIDB has become a valuable resource for running remote observer studies and providing data and statistics for imaging based-research projects. Previously, studies were run by laborious transfers of images to PACS at remote sites and paper-based data manually curated into databases. Apart from the inconvenience, these approaches also suffer from a lack of accurate location information from the paper-based forms.

Keywords

Digital Mammography Remote Site Mammographic Image Expert Radiologist Screen Detect Breast Cancer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Patel, M.N., Looney, P.T., Young, K.C., Halling-Brown, M.D.: Automated collection of medical images for research from heterogeneous systems: Trials and tribulations. In: Proc. SPIE 9039 Medical Imaging (2014)Google Scholar
  2. 2.
    Mackenzie, A., et al.: Using image simulation to test the effect of detector type on breast cancer detection. In: Proc. SPIE 9037 Medical Imaging (2014)Google Scholar
  3. 3.
    Warren, L.M., Cooke, J., Given-Wilson, R., Wallis, M., Halling-Brown, M.: Effect of image processing on detection of non-calcification cancers in 2D digital mammography imaging. In: Proc SPIE Medical Imaging (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Mark D. Halling-Brown
    • 1
  • Pádraig T. Looney
    • 2
  • Mishal N. Patel
    • 3
  • Lucy M. Warren
    • 2
    • 3
  • Alistair Mackenzie
    • 2
    • 3
  • Kenneth C. Young
    • 2
    • 3
  1. 1.Scientific Computing, Medical PhysicsRoyal Surrey County HospitalGuildfordUK
  2. 2.National Coordinating Centre for the Physics of Mammography, Medical PhysicsRoyal Surrey County HospitalGuildfordUK
  3. 3.Department of Physics, Faculty of Engineering and Physical SciencesUniversity of SurreyGuildfordUK

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