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Radiomics in Medical Imaging—Detection, Extraction and Segmentation

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Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 140))

Abstract

Radiomics, as a newly emerging technology, converts medical images into high-dimensional data via high-throughput extraction of quantitative features, followed by subsequent data analysis for decision support. It identifies general diagnostic or prognostic phenotypes with target clinical need, providing an unprecedented opportunity to improve individualized treatment in cancer at low cost. In this chapter, we will introduce radiomics from its development to its clinical applications. We divide the clinical applications into three sections based on three most common medical modality, including computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET), to give a comprehensive introduction of how radiomics works with the example of a typical cancer type. The workflow and detailed technology skills are well described in each section.

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Authors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, No. 95 Zhongguancun East Road, Beijing, 100190, China

    Jie Tian, Di Dong, Zhenyu Liu, Yali Zang, Jingwei Wei, Wei Mu & Shuo Wang

  2. Sino-Dutch Biomedical and Information Engineering School, Northeastern University, NO. 3-11, Wenhua Road, Heping District, Shenyang, 110819, China

    Jiangdian Song

  3. Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, and Department of Biomedical Data Science, Stanford University, 1265 Welch Rd, Stanford, CA, 94305-5479, USA

    Mu Zhou

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  1. Jie Tian
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  9. Mu Zhou
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Correspondence to Jie Tian .

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  1. Medical Imaging Research Center and Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, Illinois, USA

    Kenji Suzuki

  2. Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, Beijing, China

    Yisong Chen

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Tian, J. et al. (2018). Radiomics in Medical Imaging—Detection, Extraction and Segmentation. In: Suzuki, K., Chen, Y. (eds) Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging. Intelligent Systems Reference Library, vol 140. Springer, Cham. https://doi.org/10.1007/978-3-319-68843-5_11

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  • DOI: https://doi.org/10.1007/978-3-319-68843-5_11

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