Bookedited by Carlo N. De Cecco, Marly van Assen, Tim Leiner.
Summary: This book provides an overview of current and potential applications of artificial intelligence (AI) for cardiothoracic imaging. Most AI systems used in medical imaging are data-driven and based on supervised machine learning. Clinicians and AI specialists can contribute to the development of an AI system in different ways, focusing on their respective strengths. Unfortunately, communication between these two sides is far from fluent and, from time to time, they speak completely different languages. Mutual understanding and collaboration are imperative because the medical system is based on physicians' ability to take well-informed decisions and convey their reasoning to colleagues and patients. This book offers unique insights and informative chapters on the use of AI for cardiothoracic imaging from both the technical and clinical perspective. It is also a single comprehensive source that provides a complete overview of the entire process of the development and use of AI in clinical practice for cardiothoracic imaging. The book contains chapters focused on cardiac and thoracic applications as well more general topics on the potentials and pitfalls of AI in medical imaging. Separate chapters will discuss the valorization, regulations surrounding AI, cost-effectiveness, and future perspective for different countries and continents. This book is an ideal guide for clinicians (radiologists, cardiologists etc.) interested in working with AI, whether in a research setting developing new AI applications or in a clinical setting using AI algorithms in clinical practice. The book also provides clinical insights and overviews for AI specialists who want to develop clinically relevant AI applications.
Contents:
PART I: Artificial Intelligence: Technical Considerations and Fundamentals
Artificial Intelligence: A Century-Old Story
Demystifying Artificial Intelligence Technology in Cardiothoracic Imaging: The Essentials
Artificial Intelligence Algorithm Development for Biomedical Imaging
Data Preparation for Artificial Intelligence
Data Storage, Cloud Usage and Artificial Intelligence Pipeline
How to Build Artificial Intelligence Algorithms for Imaging Applications
Radiomics: Technical Background
Biobanks and Artificial Intelligence
Biostatistics and Artificial Intelligence
PART II: Artificial Intelligence: General Approaches and Applications
Structured Reporting in Medical Imaging: the Role of Artificial Intelligence
Artificial Intelligence: Clinical Relevance and Workflow
Patient Selection and Scan Preparation Optimization: the Role of Artificial Intelligence
Artificial Intelligence for Image Enhancement and Reconstruction in Magnetic Resonance Imaging
Artificial Intelligence Based Image Reconstruction in Cardiac Magnetic Resonance
Artificial Intelligence Based Image Reconstruction in Computed Tomography Imaging
Artificial Intelligence Based Contrast Medium Optimization
Radiation Dose Optimization: the Role of Artificial Intelligence
Artificial Intelligence Integration into the Computed Tomography System
Artificial Intelligence Integration into the Magnetic Resonance System
Magnetic Resonance Fingerprinting: the Role of Artificial Intelligence
Currently Available Artificial Intelligence Software for Cardiothoracic Imaging
PART III: Artificial Intelligence: Cardiac Applications
Cardiac CT Guidelines and Clinical Applications: Where does Artificial Intelligence fit in?
Natural Language Processing for Cardiovascular Applications
Artificial Intelligence Based Evaluation of Coronary Calcium
Artificial Intelligence Based Evaluation of Coronary Atherosclerotic Plaques
Artificial Intelligence Based Coronary Artery Disease Reporting & Data System (CAD-RADS)
Artificial Intelligence Based CT Derived Fractional Flow Reserve (CT-FFR)
Artificial Intelligence Based Evaluation of Cardiac Valves
Artificial Intelligence Based Diagnosis and Procedural Planning for Aortic Valve Disease
Artificial Intelligence Based Quantification of Cardiac Fat
Radiomics in Cardiac CT
Cardiac MR Guidelines and Clinical Applications: Where does Artificial Intelligence fit in?
Artificial Intelligence Based Evaluation of Functional Cardiac Magnetic Resonance Imaging
Magnetic Resonance Imaging based 4D Cardiac Flow: the Role of Artificial Intelligence
Magnetic Resonance Imaging based Coronary Flow: the Role of Artificial Intelligence
Artificial Intelligence Based Evaluation of Cardiac Congenital Disease
Cardiac Nuclear Medicine: the Role of Artificial Intelligence
Cardiac Ultrasound Imaging: the Role of Artificial Intelligence
Artificial Intelligence Based Cardiovascular Risk Stratification
PART IV: Artificial Intelligence: Thoracic Applications
Artificial Intelligence Based Evaluation of Patients with Chronic Obstructive Pulmonary Disease
Artificial Intelligence Based Evaluation of Patients with Interstitial Lung Disease
Artificial Intelligence Based Evaluation of Infectious Disease Imaging: A COVID-19 Perspective
Artificial Intelligence for Lung Cancer Screening and Nodule Detection
Artificial Intelligence for Lung Cancer Characterization and Prognosis
Artificial Intelligence for Opportunistic Chest CT Screening and Prognostication
Artificial Intelligence Based Detection of Pulmonary Vascular Disease
Artificial Intelligence Based Evaluation of the Aorta
Artificial Intelligence and Radiomics Based Evaluation of Carotid Artery Disease
PART V: Artificial Intelligence: General Considerations
Artificial Intelligence in Medicine: Laws, Regulations and Privacy
Health Economics, Economic Evaluation and Artificial Intelligence Technology
Commercialization & Intellectual Property of Artificial Intelligence Applications in Cardiovascular Imaging
Ethical Considerations of Artificial Intelligence Applications in Healthcare
How to Write and Review an Artificial Intelligence Paper
Cybersecurity in the Era of Artificial Intelligence
How Artificial Intelligence Will Reshape Healthcare and Medical Imaging: A Global Perspective.