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The Value of Structured Reporting for AI

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Artificial Intelligence in Medical Imaging

Abstract

Besides image data from which AI systems could potentially extract meaningful information, radiological departments possess vast amounts of clinically relevant information contained in the report texts associated with the respective imaging studies. However, the automated extraction of data contained in radiological reports is difficult due to the unstructured and heterogeneous nature of current day’s prose-like reports. Even though natural language processing has seen substantial improvements over the past years, it remains difficult to use radiological reports from clinical routine as valid annotations for the training of algorithms in computer vision.

Structured reporting is currently being discussed within the radiological communities and besides providing other benefits, for example, in the communication with referring physicians, would make radiological reports much more machine-readable. Also, through providing clearly defined structures, report templates would facilitate data from other systems to be integrated into the radiological report.

This chapter aims to provide an overview of the current state of structured reporting with a special focus on its potential implications for the development of and interaction with AI systems.

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Author information

Authors and Affiliations

  1. University Hospital of Cologne, Cologne, Germany

    Daniel Pinto dos Santos

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  1. Daniel Pinto dos Santos
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Editors and Affiliations

  1. ETZ Hospital, Tilburg, The Netherlands

    Erik R. Ranschaert

  2. Radiology Research and Practical Centre, Moscow, Russia

    Sergey Morozov

  3. Department of Radiology, Northwest Hospital Group, Alkmaar, The Netherlands

    Paul R. Algra

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Pinto dos Santos, D. (2019). The Value of Structured Reporting for AI. In: Ranschaert, E., Morozov, S., Algra, P. (eds) Artificial Intelligence in Medical Imaging. Springer, Cham. https://doi.org/10.1007/978-3-319-94878-2_7

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  • DOI: https://doi.org/10.1007/978-3-319-94878-2_7

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  • Online ISBN: 978-3-319-94878-2

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