Applications of Artificial Intelligence in Medical Imaging

Abdulhamit Subasi

• Publisher: Academic Press
• Year: 2022
• Print ISBN:
  9780443184505
• eBook ISBN:
  9780443184512
• Topic: Biowissenschaften
• Subtopic: Molekularbiologie

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. - 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

Table of contents

• Cover
• Title page
• Table of Contents
• Copyright
• Dedication
• Contents
• List of contributors
• Series preface
• Preface
• Acknowledgments
• List of Illustrations
• List of Tables
• Chapter 1 : Introduction to artificial intelligence techniques for medical image analysis
• Chapter 2 : Lung cancer detection from histopathological lung tissue images using deep learning
• Chapter 3 : Magnetic resonance imagining-based automated brain tumor detection using deep learning techniques
• Chapter 4 : Breast cancer detection from mammograms using artificial intelligence
• Chapter 5 : Breast tumor detection in ultrasound images using artificial intelligence
• Chapter 6 : Artificial intelligence-based skin cancer diagnosis
• Chapter 7 : Brain stroke detection from computed tomography images using deep learning algorithms
• Chapter 8 : A deep learning approach for COVID-19 detection from computed tomography scans
• Chapter 9 : Detection and classification of Diabetic Retinopathy Lesions using deep learning
• Chapter 10 : Automated detection of colon cancer using deep learning
• Chapter 11 : Brain hemorrhage detection using computed tomography images and deep learning
• Chapter 12 : Artificial intelligence-based retinal disease classification using optical coherence tomography images
• Chapter 13 : Diagnosis of breast cancer from histopathological images with deep learning architectures
• Chapter 14 : Artificial intelligence based Alzheimer’s disease detection using deep feature extraction
• Index
• A