Applications of Artificial Intelligence in Medical Imaging

Applications of Artificial Intelligence in Medical Imaging

1st Edition - November 1, 2022

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  • Editor: Abdulhamit Subasi
  • Paperback ISBN: 9780443184505

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Applications of Artificial Intelligence in Medical Imaging provides the description of various biomedical image analysis in disease detection using AI that can be used to incorporate knowledge obtained from different medical imaging devices such as CT, X-ray, PET and ultrasound. The book discusses the use of AI for detection of several cancer types, including brain tumor, breast, pancreatic, rectal, lung colon, and skin. In addition, it explains how AI and deep learning techniques can be used to diagnose Alzheimer's, Parkinson's, COVID-19 and mental conditions. This is a valuable resource for clinicians, researchers and healthcare professionals who are interested in learning more about AI and its impact in medical/biomedical image analysis.

Key Features

  • Discusses new deep learning algorithms for image analysis and how they are used for medical images
  • Provides several examples for each imaging technique, along with their application areas so that readers can rely on them as a clinical decision support system
  • Describes how new AI tools may contribute significantly to the successful enhancement of a single patient's clinical knowledge to improve treatment outcomes


Researchers, professionals, academicians, and graduate students on medical informatics and computer science

Table of Contents

  • 1. Introduction to AI techniques for medical Imaging
    2. Brain tumor segmentation and grading of lower-grade glioma using deep learning
    3. Deep learning approach for brain cancer MRI images classification
    4. Breast cancer detection using mammogram images and deep learning
    5. Artificial intelligence techniques for breast cancer detection using Ultrasound imaging
    6. Breast cancer detection using deep features and histopathological images
    7. Deep learning for detection of pancreatic cancer
    8. Automatic tumor delineation in rectal cancer using deep learning
    9. Automated detection of lung cancer using deep neural networks
    10. Automated detection of colon cancer using deep neural networks
    11. Artificial intelligence-based image classification methods for diagnosis of skin cancer
    12. A deep learning framework for prostate cancer detection using histopathological images
    13. Artificial Intelligence in Alzheimer Detection
    14. Classification of PPMI MRI scans for the diagnosis of Parkinson’s disease
    15. Deep learning model for identifying mild cognitive impairment in patients with Parkinson's disease
    16. Detection and Classification of Diabetic Retinopathy Lesions using deep learning
    17. Use of CT Imaging and Artificial Intelligence in COVID-19 Infection
    18. Deep learning approaches for COVID-19 detection based on chest X-ray images
    19. Pneumonia Detection in Chest X-Ray
    20. AI for major depressive disorder
    21. AI study of patients with schizophrenia, bipolar disorder and healthy subjects
    22. Identification of suicidality in adolescent major depressive disorder patients using AI
    23. Artificial Intelligence in Head and Neck Imaging

Product details

  • No. of pages: 400
  • Language: English
  • Copyright: © Academic Press 2022
  • Published: November 1, 2022
  • Imprint: Academic Press
  • Paperback ISBN: 9780443184505

About the Editor

Abdulhamit Subasi

Abdulhamit Subasi
Prof. Dr. Abdulhamit Subasi is specialized in Machine Learning, Data mining and Biomedical Signal Processing. Concerning application of machine learning to different fields, he wrote seven book chapters and more than 150 published journal and conference papers. He is also author of the book, “Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques”. He worked at many institutions as an academician and Georgia Institute of Technology, Georgia, USA, as a researcher. He has been awarded with the Queen Effat Award for Excellence in Research, May 2018. Since 2015, he has been working as a Professor of Information Systems at Effat University, Jeddah, Saudi Arabia. He has worked on several projects related to biomedical signal processing and data analysis.

Affiliations and Expertise

Professor of Information Systems at Effat University, Jeddah, Saudi Arabia

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