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Potentials of radiomics for cancer diagnosis and treatment in comparison with computer-aided diagnosis

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Abstract

Computer-aided diagnosis (CAD) is a field that is essentially based on pattern recognition that improves the accuracy of a diagnosis made by a physician who takes into account the computer’s “opinion” derived from the quantitative analysis of radiological images. Radiomics is a field based on data science that massively and comprehensively analyzes a large number of medical images to extract a large number of phenotypic features reflecting disease traits, and explores the associations between the features and patients’ prognoses for precision medicine. According to the definitions for both, you may think that radiomics is not a paraphrase of CAD, but you may also think that these definitions are “image manipulation”. However, there are common and different features between the two fields. This review paper elaborates on these common and different features and introduces the potential of radiomics for cancer diagnosis and treatment by comparing it with CAD.

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Acknowledgements

The researches described in this review paper were partially supported by the “Program for Supporting Educations and Researches on Mathematics and Data Science in Kyushu University”. The authors are grateful to all members of the Arimura laboratory (http://web.shs.kyushu-u.ac.jp/~arimura), whose comments made enormous contributions to the researches described in this review paper.

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Authors and Affiliations

  1. Division of Medical Quantum Science, Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan

    Hidetaka Arimura

  2. Division of Information Science, Nara Institute of Science and Technology, Ikoma, Japan

    Mazen Soufi

  3. Department of Radiological Technology, Faculty of Fukuoka Medical Technology, Teikyo University, Omuta, Japan

    Hidemi Kamezawa

  4. Division of Medical Quantum Science, Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan

    Kenta Ninomiya & Masahiro Yamada

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  1. Hidetaka Arimura
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  2. Mazen Soufi
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Correspondence to Hidetaka Arimura.

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Arimura, H., Soufi, M., Ninomiya, K. et al. Potentials of radiomics for cancer diagnosis and treatment in comparison with computer-aided diagnosis. Radiol Phys Technol 11, 365–374 (2018). https://doi.org/10.1007/s12194-018-0486-x

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