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Artificial Intelligence and Computer-Assisted Evaluation of Chest Pathology

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Book cover Artificial Intelligence in Medical Imaging

Abstract

The use of computer-assisted diagnosis in chest pathologies has gradually made inroads into the clinical workflow of chest radiography and computed tomography. The introduction of novel machine learning tools and application of artificial intelligence will likely lead to more advanced applications, which will be better suited to what chest radiologists require to allow efficient and accurate reporting. The excitement around these software opportunities extends beyond the simple “diagnostic” utility but expands into quantifiable disease biomarkers, which will have impact on patients’ management, the selection of patients for clinical trials of new drugs and ultimately the impact of (new) treatments on long-term outcomes.

This chapter will offer insight into the use of computer-assisted systems in the main areas of lung nodules/lung cancer, pulmonary embolism and parenchymal and airways diseases.

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Authors and Affiliations

  1. Edinburgh Imaging, University of Edinburgh, Edinburgh, UK

    Edwin J. R. van Beek & John T. Murchison

  2. Department of Radiology, Royal Infirmary of Edinburgh, Edinburgh, UK

    Edwin J. R. van Beek & John T. Murchison

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  1. Edwin J. R. van Beek
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  2. John T. Murchison
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Correspondence to Edwin J. R. van Beek .

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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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van Beek, E.J.R., Murchison, J.T. (2019). Artificial Intelligence and Computer-Assisted Evaluation of Chest Pathology. 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_12

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  • DOI: https://doi.org/10.1007/978-3-319-94878-2_12

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