Artificial Intelligence Review

, Volume 47, Issue 4, pp 531–559 | Cite as

Image descriptors in radiology images: a systematic review

  • Mariana A. Nogueira
  • Pedro Henriques AbreuEmail author
  • Pedro Martins
  • Penousal Machado
  • Hugo Duarte
  • João Santos


Clinical decisions are sometimes based on a variety of patient’s information such as: age, weight or information extracted from image exams, among others. Depending on the nature of the disease or anatomy, clinicians can base their decisions on different image exams like mammographies, positron emission tomography scans or magnetic resonance images. However, the analysis of those exams is far from a trivial task. Over the years, the use of image descriptors—computational algorithms that present a summarized description of image regions—became an important tool to assist the clinician in such tasks. This paper presents an overview of the use of image descriptors in healthcare contexts, attending to different image exams. In the making of this review, we analyzed over 70 studies related to the application of image descriptors of different natures—e.g., intensity, texture, shape—in medical image analysis. Four imaging modalities are featured: mammography, PET, CT and MRI. Pathologies typically covered by these modalities are addressed: breast masses and microcalcifications in mammograms, head and neck cancer and Alzheimer’s disease in the case of PET images, lung nodules regarding CTs and multiple sclerosis and brain tumors in the MRI section.


Image descriptors Medical images Computer vision Healthcare contexts 


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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Mariana A. Nogueira
    • 1
  • Pedro Henriques Abreu
    • 1
    Email author
  • Pedro Martins
    • 1
  • Penousal Machado
    • 1
  • Hugo Duarte
    • 2
  • João Santos
    • 2
  1. 1.Department of Informatics Engineering, Faculty of Sciences and Technology, Centre for Informatics and SystemsUniversity of CoimbraCoimbraPortugal
  2. 2.IPO-Porto Research Centre (CI-IPOP)PortoPortugal

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