Artificial Intelligence in Medical Imaging

Opportunities, Applications and Risks

  • Erik R. Ranschaert
  • Sergey Morozov
  • Paul R. Algra

Table of contents

  1. Front Matter
    Pages i-xv
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Sergey Morozov, Erik Ranschaert, Paul Algra
      Pages 3-5
  3. Technology: Getting Started

    1. Front Matter
      Pages 7-7
    2. Frederik Maes, David Robben, Dirk Vandermeulen, Paul Suetens
      Pages 9-23
    3. Bart M. ter Haar Romeny
      Pages 25-38
  4. Technology: Developing A.I. Applications

    1. Front Matter
      Pages 47-47
    2. Angel Alberich-Bayarri, Ana Jiménez Pastor, Rafael López González, Fabio García Castro
      Pages 49-59
    3. Daniel Pinto dos Santos
      Pages 73-82
    4. Luke Oakden-Rayner, Lyle John Palmer
      Pages 83-104
  5. Big Data in Medicine

    1. Front Matter
      Pages 105-105
    2. Peter Mildenberger
      Pages 107-117
    3. Angel Alberich-Bayarri, Emanuele Neri, Luis Martí-Bonmatí
      Pages 119-126
  6. Practical Use Cases of A.I. in Radiology

    1. Front Matter
      Pages 127-127
    2. José M. Morey, Nora M. Haney, Woojin Kim
      Pages 129-143
    3. Edwin J. R. van Beek, John T. Murchison
      Pages 145-166
    4. Johan Verjans, Wouter B. Veldhuis, Gustavo Carneiro, Jelmer M. Wolterink, Ivana Išgum, Tim Leiner
      Pages 167-185
    5. Hugh Harvey, Andreas Heindl, Galvin Khara, Dimitrios Korkinof, Michael O’Neill, Joseph Yearsley et al.
      Pages 187-215
    6. Nathaniel Swinburne, Andrei Holodny
      Pages 217-230
    7. Irene Mayorga-Ruiz, Ana Jiménez-Pastor, Belén Fos-Guarinos, Rafael López-González, Fabio García-Castro, Ángel Alberich-Bayarri
      Pages 231-243
  7. Quality, Regulatory and Ethical Issues

    1. Front Matter
      Pages 245-245
    2. Peter M. A. van Ooijen
      Pages 247-255
    3. Robert van den Hoven van Genderen
      Pages 257-290
    4. Bibb Allen, Robert Gish, Keith Dreyer
      Pages 291-327
    5. Erik R. Ranschaert, André J. Duerinckx, Paul Algra, Elmar Kotter, Hans Kortman, Sergey Morozov
      Pages 329-346
  8. Back Matter
    Pages 347-373

About this book


This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.


Artificial Intelligence in Medical Imaging Deep Learning in Medical Imaging Machine Learning in Medical Imaging Techniques for AI in Medical Imaging Big Data in Radiology Artificial Intelligence in Radiology Medical Imaging Informatics Imaging Biomarkers Medical Imaging Computing Data Mining in Radiology Image Biobanks

Editors and affiliations

  • Erik R. Ranschaert
    • 1
  • Sergey Morozov
    • 2
  • Paul R. Algra
    • 3
  1. 1.ETZ HospitalTilburgThe Netherlands
  2. 2.Radiology Research and Practical CentreMoscowRussia
  3. 3.Department of RadiologyNorthwest Hospital GroupAlkmaarThe Netherlands

Bibliographic information