A primer on texture analysis in abdominal radiology Review


Authors: Horvat, N.; Miranda, J.; El Homsi, M.; Peoples, J. J.; Long, N. M.; Simpson, A. L.; Do, R. K. G.
Review Title: A primer on texture analysis in abdominal radiology
Abstract: 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. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Keywords: positron emission tomography; magnetic resonance imaging; computed tomography; texture analysis; machine learning; radiomics
Journal Title: Abdominal Radiology
Volume: 47
Issue: 9
ISSN: 2366-004X
Publisher: Springer  
Date Published: 2022-09-01
Start Page: 2972
End Page: 2985
Language: English
DOI: 10.1007/s00261-021-03359-3
PUBMED: 34825946
PROVIDER: scopus
DOI/URL:
Notes: Article -- Export Date: 2 September 2022 -- Source: Scopus
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  1. Kinh Gian Do
    257 Do
  2. Niamh   Long
    18 Long
  3. Natally Horvat
    101 Horvat