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Visual analysis of retinal changes with optical coherence tomography

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Abstract

Optical coherence tomography (OCT) enables noninvasive high-resolution 3D imaging of the human retina, and thus plays a fundamental role in detecting a wide range of ocular diseases. Despite the diagnostic value of OCT, managing and analyzing resulting data is challenging. We apply two visual analysis strategies for supporting retinal assessment in practice. First, we provide an interface for unifying and structuring data from different sources into a common basis. Fusing that basis with medical records and augmenting it with analytically derived information facilitates thorough investigations. Second, we present a tailored visual analysis tool for presenting, emphasizing, selecting, and comparing different aspects of the attributed data. This enables free exploration, reducing the data to relevant subsets, and focusing on details. By applying both strategies, we effectively enhance the management and the analysis of retinal OCT data for assisting medical diagnoses. Domain experts applied our solution successfully to study early retinal changes in patients suffering from type 1 diabetes mellitus.

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Acknowledgements

The authors wish to thank Heidelberg Engineering GmbH for providing OCT hardware, and respective software interfaces and analysis software.

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Authors and Affiliations

  1. Institute for Computer Science, University of Rostock, Rostock, Germany

    Martin Röhlig, Christoph Schmidt, Paul Rosenthal & Heidrun Schumann

  2. Department of Ophthalmology, University of Rostock, Rostock, Germany

    Ruby Kala Prakasam & Oliver Stachs

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  1. Martin Röhlig
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  2. Christoph Schmidt
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  3. Ruby Kala Prakasam
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  4. Paul Rosenthal
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Corresponding author

Correspondence to Martin Röhlig.

Additional information

This work has been supported by the German Research Foundation (Project VIES) and by the German Federal Ministry of Education and Research (Project TOPOs)

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Röhlig, M., Schmidt, C., Prakasam, R.K. et al. Visual analysis of retinal changes with optical coherence tomography. Vis Comput 34, 1209–1224 (2018). https://doi.org/10.1007/s00371-018-1486-x

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