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Digital and Computational Pathology for Biomarker Discovery

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Predictive Biomarkers in Oncology

Abstract

Digital pathology is now centre stage in tissue analytics by providing a range of new advanced tools for biomarker research, analysis, discovery and translation. The advantages of digital image analytics in tissue research have been recognized for many years. However, recent advances in high-resolution whole slide scanning, web-enabled multisite collaboration, image analytics, machine learning and imaging informatics are now, for the first time, enabling researchers to accelerate quantitative biomarker discovery and transform the discovery and clinical translation of companion diagnostics for precision therapeutics. This chapter will summarize some of the most important advances in digital pathology and the transformative impact this is having on cancer biomarker discovery and development.

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Disclosure

The opinions expressed in this presentation are solely those of the author or presenters and do not necessarily reflect those of Philips. The information presented herein is not specific to any product of Philips or their intended uses. The information contained herein does not constitute, and should not be construed as, any promotion of Philips products or company policies.

Author information

Authors and Affiliations

  1. Department of Digital Pathology, Philips UK, Belfast, Northern Ireland, UK

    Peter Hamilton

  2. Belfast Development Hub, Philips Digital Pathology Solutions, Belfast, UK

    Paul O’Reilly & Peter Bankhead

  3. Digital Pathology Solutions, Pharma Solutions, Philips Digital Pathology Solutions, Best, The Netherlands

    Esther Abels

  4. Northern Ireland Molecular Pathology Laboratory, Centre for Cancer Research, Department of Cell Biology, Queens University Belfast, Belfast, Antrim, UK

    Manuel Salto-Tellez

Authors
  1. Peter Hamilton
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  2. Paul O’Reilly
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  3. Peter Bankhead
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  4. Esther Abels
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  5. Manuel Salto-Tellez
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Corresponding author

Correspondence to Peter Hamilton .

Editor information

Editors and Affiliations

  1. Department of Pathology and Lab Medicine, Indiana University School of Medicine, Indianapolis, IN, USA

    Sunil Badve

  2. Targos Inc., Issaquah, WA, USA

    George Louis Kumar

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Hamilton, P., O’Reilly, P., Bankhead, P., Abels, E., Salto-Tellez, M. (2019). Digital and Computational Pathology for Biomarker Discovery. In: Badve, S., Kumar, G. (eds) Predictive Biomarkers in Oncology. Springer, Cham. https://doi.org/10.1007/978-3-319-95228-4_7

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  • DOI: https://doi.org/10.1007/978-3-319-95228-4_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95227-7

  • Online ISBN: 978-3-319-95228-4

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