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Editorial
. 2018 Feb;59(2):189-193.
doi: 10.2967/jnumed.117.200501. Epub 2017 Nov 24.

Responsible Radiomics Research for Faster Clinical Translation

Martin Vallières  1 , Alex Zwanenburg  2   3 , Bodgan Badic  1 , Catherine Cheze Le Rest  1 , Dimitris Visvikis  1 , Mathieu Hatt  4
Affiliations
Editorial

Responsible Radiomics Research for Faster Clinical Translation

Martin Vallières et al. J Nucl Med. 2018 Feb.
No abstract available

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Figures

FIGURE 1.
FIGURE 1.
Radiomics workflow. (A) From medical imaging acquisition to treatment personalization. (B) Workflow of computation of radiomics features. Depending on the specific imaging modality and purpose, some steps may be omitted. In the figure, the feature calculation part is expanded to show different feature families with specific processing steps. IH = intensity histogram; IVH = intensity-volume histogram; GLCM = grey level cooccurrence matrix; GLRLM = grey level run length matrix; GLSZM = grey level size zone matrix; NGTDM = neighborhood grey tone difference matrix; NGLDM = neighboring grey level dependence matrix; GLDZM = grey level distance zone matrix. *Discretisation of IVH differs from IH and textural features. (Adapted from (20); ©2016-2017 IBSI. Creative Commons Attribution 4.0 International License.)
See this image and copyright information in PMC

References

    1. Nowell PC. Tumor progression: a brief historical perspective. Semin Cancer Biol. 2002;12:261–266. - PubMed
    1. Gillies RJ, Kinahan PE, Hricak H. Radiomics: images are more than pictures, they are data. Radiology. 2016;278:563–577. - PMC - PubMed
    1. Giger ML, Chan H-P, Boone J. Anniversary paper: history and status of CAD and quantitative image analysis—the role of medical physics and AAPM. Med Phys. 2008;35:5799–5820. - PMC - PubMed
    1. Obermeyer Z, Emanuel EJ. Predicting the future: big data, machine learning, and clinical medicine. N Engl J Med. 2016;375:1216–1219. - PMC - PubMed
    1. El Naqa I, Grigsby P, Apte A, et al. Exploring feature-based approaches in PET images for predicting cancer treatment outcomes. Pattern Recognit. 2009;42:1162–1171. - PMC - PubMed

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