Radiomics in oncology - uncovering tumor phenotype from medical images: a short introduction

Authors

  • Matea Pavic Department of Radiation Oncology, University Hospital Zurich and University Zurich, Rämistrasse 100, 8091 Zurich, Switzerland
  • Janita E. van Timmeren Department of Radiation Oncology, University Hospital Zurich and University Zurich, Rämistrasse 100, 8091 Zurich, Switzerland

DOI:

https://doi.org/10.5166/jroi.11.1.2

Keywords:

Radiomics, Image analysis, Machine learning, Prognostic modelling, Clinical decision support system

Abstract

Radiomics is a promising method to quantify and describe the tumor phenotype on medical images. High numbers of image features are extracted from medical images and can be used within a clinical decision support system by integrating this data with clinical and pathological variables. Herein, we give a short introduction into this image analysis method and present an overview on the workflow.

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Published

2021-08-18

Issue

Vol. 11 No. 1 (2021)

Section

Articles

License

Copyright (c) 2021 Matea Pavic, Janita E. van Timmeren

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright remains with the author(s).

Articles published until 2016 were published under CC BY-NC-ND 2.0.

How to Cite

Pavic, M., & Van Timmeren, J. (2021). Radiomics in oncology - uncovering tumor phenotype from medical images: a short introduction . Journal of Radiation Oncology Informatics, 11(1), 4. https://doi.org/10.5166/jroi.11.1.2