A primer on texture analysis in abdominal radiology

Natally Horvat, Joao Miranda, Maria El Homsi, Jacob J. Peoples, Niamh M. Long, Amber L. Simpson, Richard K.G. Do

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


The number of publications on texture analysis (TA), radiomics, and radiogenomics has been growing exponentially, with abdominal radiologists aiming to build new prognostic or predictive biomarkers for a wide range of clinical applications including the use of oncological imaging to advance the field of precision medicine. TA is specifically concerned with the study of the variation of pixel intensity values in radiological images. Radiologists aim to capture pixel variation in radiological images to deliver new insights into tumor biology that cannot be derived from visual inspection alone. TA remains an active area of investigation and requires further standardization prior to its clinical acceptance and applicability. This review is for radiologists interested in this rapidly evolving field, who are thinking of performing research or want to better interpret results in this arena. We will review the main concepts in TA, workflow processes, and existing challenges and steps to overcome them, as well as look at publications in body imaging with external validation.

Original languageEnglish
Pages (from-to)2972-2985
Number of pages14
JournalAbdominal Radiology
Issue number9
StatePublished - Sep 2022
Externally publishedYes


  • Computed tomography
  • Machine learning
  • Magnetic resonance imaging
  • Positron emission tomography
  • Radiomics
  • Texture analysis


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