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Radiology· 2015Q1

Radiomics: Images Are More than Pictures, They Are Data

Robert J. Gillies, Paul E. Kinahan, Hedvig Hricak

Short summary

Radiomics transforms medical images from visual aids into mineable data by extracting quantitative features, enabling sophisticated analysis for improved diagnostic and prognostic accuracy.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Medical images are converted into quantitative, mineable data through radiomics.
  • High-throughput extraction of first-, second-, and higher-order statistical features is employed.
  • Radiomic data, combined with patient data, are analyzed with bioinformatics tools.
  • Potential to improve diagnostic, prognostic, and predictive accuracy, especially in oncology.

AI-generated from the title and abstract; the full text is not read.

Abstract

In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data set sizes. These advances have facilitated the development of processes for high-throughput extraction of quantitative features that result in the conversion of images into mineable data and the subsequent analysis of these data for decision support; this practice is termed radiomics. This is in contrast to the traditional practice of treating medical images as pictures intended solely for visual interpretation. Radiomic data contain first-, second-, and higher-order statistics. These data are combined with other patient data and are mined with sophisticated bioinformatics tools to develop models that may potentially improve diagnostic, prognostic, and predictive accuracy. Because radiomics analyses are intended to be conducted with standard of care images, it is conceivable that conversion of digital images to mineable data will eventually become routine practice. This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.

The authors' abstract, as published at the source. Radiology, 2015 · DOI ↗

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Field: Radiology, Nuclear Medicine and Imaging

Radiology, Nuclear Medicine and ImagingMedicine