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A Web-Based Platform for Distributed Annotation of Computerized Tomography Scans

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Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis (LABELS 2017, STENT 2017, CVII 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10552))

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Abstract

Computer Aided Diagnosis (CAD) systems are adopting advancements at the forefront of computer vision and machine learning towards assisting medical experts with providing faster diagnoses. The success of CAD systems heavily relies on the availability of high-quality annotated data. Towards supporting the annotation process among teams of medical experts, we present a web-based platform developed for distributed annotation of medical images. We capitalize on the HTML5 canvas to allow for medical experts to quickly perform segmentation of regions of interest. Experimental evaluation of the proposed platform show a significant reduction in the time required to perform the annotation of abdominal computerized tomography images. Furthermore, we evaluate the relationship between the size of the harvested regions and the quality of the annotations. Finally, we present additional functionality of the developed platform for the closer examination of 3D point clouds for kidney cancer.

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Notes

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Acknowledgments

We thank Maxwell Fite and Stamatios Morellas for their expertise on heuristic evaluation, Drs. Christopher Weight, Niranjan Sathianathen, and Suprita Krishna for their feedback on the initial development process, and Samit Roy, Meera Sury, and Michael Tradewell for annotations completed thus far. “‘This material is partially based upon work supported by the National Science Foundation through grants #CNS-0934327, #CNS-1039741, #SMA-1028076, #CNS-1338042, #CNS-1439728, #OISE-1551059, and #CNS-1514626.”’

Author information

Authors and Affiliations

  1. University of Minnesota Center for Distributed Robotics, 117 Pleasant St SE, Minneapolis, MN, 55455, USA

    Nicholas Heller, Panagiotis Stanitsas, Vassilios Morellas & Nikolaos Papanikolopoulos

Authors
  1. Nicholas Heller
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  2. Panagiotis Stanitsas
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  3. Vassilios Morellas
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  4. Nikolaos Papanikolopoulos
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Corresponding author

Correspondence to Nicholas Heller .

Editor information

Editors and Affiliations

  1. University College London, London, United Kingdom

    M. Jorge Cardoso

  2. McGill University, Montreal, Québec, Canada

    Tal Arbel

  3. Imperial College London, London, United Kingdom

    Su-Lin Lee

  4. Eindhoven University of Technology, Eindhoven, The Netherlands

    Veronika Cheplygina

  5. University of Barcelona, Barcelona, Spain

    Simone Balocco

  6. Technical University of Munich, Garching, Germany

    Diana Mateus

  7. Nara Institute of Science and Technology, Nara, Japan

    Guillaume Zahnd

  8. DKFZ, Heidelberg, Germany

    Lena Maier-Hein

  9. Technical University Munich, Munich, Germany

    Stefanie Demirci

  10. École de Technologie Supérieure, Montreal, Québec, Canada

    Eric Granger

  11. École de Technologie Supérieure, Montreal, Canada

    Luc Duong

  12. École de Technologie Supérieure, Montreal, Québec, Canada

    Marc-André Carbonneau

  13. Technical University Munich, Munich, Germany

    Shadi Albarqouni

  14. University of Adelaide, Adelaide, South Australia, Australia

    Gustavo Carneiro

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Heller, N., Stanitsas, P., Morellas, V., Papanikolopoulos, N. (2017). A Web-Based Platform for Distributed Annotation of Computerized Tomography Scans. In: Cardoso, M., et al. Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis. LABELS STENT CVII 2017 2017 2017. Lecture Notes in Computer Science(), vol 10552. Springer, Cham. https://doi.org/10.1007/978-3-319-67534-3_15

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  • DOI: https://doi.org/10.1007/978-3-319-67534-3_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67533-6

  • Online ISBN: 978-3-319-67534-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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