1st Edition

The Impact of Artificial Intelligence in Radiology

Edited By Adam E. M. Eltorai, H. Henry Guo Copyright 2025
    200 Pages 16 Color Illustrations
    by CRC Press

    200 Pages 16 Color Illustrations
    by CRC Press

    Implementation of artificial intelligence (AI) in Radiology is an important topic of discussion. Advances in AI—which encompass machine learning, artificial neural networks, and deep learning—are increasingly being applied to diagnostic imaging. While some posit radiologists are irreplaceable, certain AI proponents have proposed to “stop training radiologists now.” By compiling perspectives from experts from various backgrounds, this book explores the current state of AI efforts in Radiology along with the clinical, financial, technological, and societal perspectives on the role and expected impact of AI in Radiology.

    Technology in medicine - disruptive innovation

    Chapter 1: Clinical view

    Ranson Liao 

    Chapter 2: Technological view

    Suely Fazio Ferraciolli; Edson Saito; Eduardo Farina; Léo Max Feuerschuette Neto; Osvaldo Landi Junior; Felipe Campos Kitamura

    Chapter 3: Societal view

    Ribhav Gupta; Heena Shah; Rajiv Dharnipragada; Ronit Gupta

    Chapter 4: Financial view

    Charlene Liew Jin Yee

    Radiology's role in medicine

    Chapter 5: Clinical view

    Christian Bluthgen

    Chapter 6: Technological view

    Abhishta Bhandari 

    Chapter 7: Societal view

    Krithika Rangarajan

    Chapter 8: Financial view

    Youngmin Chu 

    What is AI?

    Chapter 9: Clinical view

    Christian Federau

    Chapter 10: Technological view

    Bilwaj Gaonkar

    Chapter 11: Societal view

    Amy Patel 

    Chapter 12: Financial view

    Christian Park


    Current state of AI in radiology

    Chapter 13: Clinical view

    Alexander Jacobs 

    Chapter 14: Technological view

    Mireia Crispin Ortuzar

    Chapter 15: Societal view

    Suely Fazio Ferraciolli

    Chapter 16: Financial view

    Florian Dubost


    AI applications in development

    Chapter 17: Clinical view

    Leonid Chepelev

    Chapter 18: Technological view

    Tyler Gathman

    Chapter 19: Societal view

    Jayashree Kalpathy-Cramer

    Chapter 20: Financial view

    David Wu


    Potential of AI

    Chapter 21: Clinical view

    Joseph Maldjian

    Chapter 22: Technological view

    William Hsu

    Chapter 23: Societal view

    Amy Patel

    Chapter 24: Financial view

    David Wu


    Expectations - radiologists' jobs, job satisfaction, salary, role in society

    Chapter 25: Clinical view

    Amy Patel 

    Chapter 26: Technological view

    Dr Kline

    Chapter 27: Societal view

    Benard Botwe

    Chapter 28: Financial view

    Mohammad Aghazadeh


    Attitudes - implementation feasibility

    Chapter 29: Clinical view

    Christina Malamateniou 

    Chapter 30: Technological view

    David Wu; Alexander Jacobs

    Chapter 31: Societal view

    Risto Filippi 

    Chapter 32: Financial view

    David Wu


    Technology determinism

    Chapter 33: Clinical view

    Suely Fazio Ferraciolli

    Chapter 34: Technological view

    Rajiv Dharnipragada

    Chapter 35: Societal view

    Rajiv Dharnipragada

    Chapter 36: Financial view

    David Wu; Megan Kollitz


    Adam E. M. Eltorai, MD, PhD

    Dr Eltorai completed his graduate studies in Biomedical Engineering and Biotechnology along with his medical degree from Brown University, followed by Radiology residency at Brigham and Women's Hospital/Harvard Medical School. He is interested in the development and clinical implementation of AI applications. Dr. Eltorai has published over 130 scientific journal articles and over 25 books.

    Ian Pan, MD

    Dr Pan is currently a diagnostic radiology resident and former chief resident in the Brigham and Women’s Hospital/Harvard Medical School Diagnostic Radiology Residency Program. He graduated from the Program in Liberal Medical Education at Brown University where he received concurrent bachelor’s and master’s degrees in applied mathematics-Biology and Biostatistics in 2016, as well as his MD from the Warren Alpert Medical School in 2020. His expertise lies at the intersection of artificial intelligence and medical imaging, having won multiple international competitions sponsored by organizations such as the Radiological Society of North America and published over 30 peer-reviewed manuscripts in this domain. 

    H. Henry Guo, MD, PhD

    Dr Guo is a clinical professor in the Department of Radiology at the Stanford University School of Medicine. He received his MD and PhD in the department of Pathology at the University of Washington, followed by Radiology residency and fellowships in Nuclear Medicine and Thoracic Imaging at Stanford. Since joining the Stanford faculty in 2012, Dr. Guo focuses on cancer and lung diseases in his clinical practice and research, co-authoring over 70 research articles, book chapters, and web-based educational resources, and is a recognized expert in interpretation of thoracic CTs and PET-CTs. Dr. Guo is translating the use of quantitative CT and AI-enabled tools to clinical practice and collaborates with other faculty members as a part of the Center for Artificial Intelligence in Medicine & Imaging (AIMI) at Stanford on applications of AI to topics including interstitial lung diseases, early cancer detection, and pulmonary hypertension.