Radiomics: Extracting more information from medical images using advanced feature analysis

Philippe Lambin*, Emmanuel Rios-Velazquez, Ralph Leijenaar, Sara Carvalho, Ruud G. P. M. van Stiphout, Patrick Granton, Catharina M. L. Zegers, Robert Gillies, Ronald Boellard, Andre Dekker, Hugo J. W. L. Aerts

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Solid cancers are spatially and temporally heterogeneous. This limits the use of invasive biopsy based molecular assays but gives huge potential for medical imaging, which has the ability to capture intra-tumoural heterogeneity in a non-invasive way. During the past decades, medical imaging innovations with new hardware, new imaging agents and standardised protocols, allows the field to move towards quantitative imaging. Therefore, also the development of automated and reproducible analysis methodologies to extract more information from image-based features is a requirement. Radiomics - the high-throughput extraction of large amounts of image features from radiographic images - addresses this problem and is one of the approaches that hold great promises but need further validation in multi-centric settings and in the laboratory.
Original languageEnglish
Pages (from-to)441-446
Number of pages6
JournalEuropean Journal of Cancer
Issue number4
Publication statusPublished - Mar 2012


  • Imaging
  • Radiomics
  • Tumour
  • Intra tumour heterogeneity


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