Artificial Intelligence in Cardiothoracic Imaging

ISBN-13: 9783030920869 / Angielski / Twarda / 2022

Opis

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.

Spis treści

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 Qian Tao

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

O autorze

Carlo N. De Cecco, MD PhD is Associate Professor of Radiology and Biomedical Informatics, and Director of the Translational Laboratory for Cardiothoracic Imaging and Artificial Intelligence in the Department of Radiology and Imaging Sciences at Emory University Hospital in Atlanta, USA. He is editor of the Springer books MDCT and MRI of the Heart (2014) and Dual Energy CT in Oncology (2015).

Marly van Assen, PhD is a Post-Doctoral Fellow in the Translational Laboratory for Cardiothoracic Imaging and Artificial Intelligence in the Department of Radiology and Imaging Sciences at Emory University Hospital in Atlanta, USA.

Tim Leiner, MD PhD is Professor of Radiology at Utrecht University Medical Center in the Netherlands with a strong interest in development and clinical implementation of AI.