Skip to main content
Chaptra
Cover of Artificial Intelligence in Cardiothoracic Imaging

Artificial Intelligence in Cardiothoracic Imaging

Written by Tim Leiner,Carlo N. De Cecco,Marly van Assen

Not rated yet — tap a star to review it

582 pages, about 12 hours of reading

Chaptra reads alongside you — AI insights, chapter breakdowns and reader discussions for every book. Join free

About this book

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.

Read it with a club

Small groups reading the same books and talking as they go.

All clubs
A bright library atrium seen from above

News

  • 1 member
  • 1,813 discussions
  • Active 7h ago

Read Artificial Intelligence in Cardiothoracic Imaging alongside people who are reading it too.

Chaptra Prime — paid clubs, every club feature, and unlimited reading support, for $5 a month or $60 once.

See Prime

Reading guide

Themes, characters and key ideas in Artificial Intelligence in Cardiothoracic Imaging, written by Chaptra AI.

  • about 25 hours
  • advanced
  • informative
  • technical
  • analytical

This book serves as a comprehensive guide to the application of artificial intelligence (AI) in the specialized field of cardiothoracic imaging. It systematically explores how AI, particularly machine learning and deep learning techniques, can enhance image acquisition, processing, analysis, and interpretation for both cardiac and thoracic conditions. Authored by experts Tim Leiner, Carlo N. De Cecco, and Marly van Assen, the text aims to bridge the gap between AI methodologies and clinical radiology practice, providing insights into diagnostic improvements, workflow optimization, and predictive analytics. It is designed for radiologists, cardiologists, computer scientists, and researchers interested in the cutting-edge intersection of AI and medical imaging.

The integration of artificial intelligence promises to revolutionize cardiothoracic imaging, moving beyond quantitative analysis to predictive diagnostics.

Key themes

Integration of AI in Clinical Practice
This theme explores the practical challenges and opportunities of embedding AI technologies into routine cardiothoracic imaging workflows. It covers aspects like system interoperability, user interface design, diagnostic accuracy improvement, and workflow efficiency.
Methodological Foundations of AI in Imaging
This theme delves into the underlying machine learning and deep learning techniques pertinent to medical image analysis. It covers topics such as convolutional neural networks, data augmentation, transfer learning, segmentation algorithms, and performance metrics.
Ethical and Regulatory Considerations
This theme examines the ethical implications, biases, and regulatory challenges associated with deploying AI in clinical cardiothoracic imaging. It includes discussions on patient data privacy, algorithmic bias, accountability for errors, and the process of obtaining regulatory approval for AI medical devices.

Worth discussing

What are the most promising current applications of AI in cardiothoracic imaging, and what are their limitations?

Chapter-by-chapter breakdowns, character arcs and the full thematic analysis come with a free account.

Discussions

No one has started one yet

Join

Questions this book opens up

No discussions yet

Be the first to start a discussion about this book!

Sign up to start the discussion

Reviews

No reviews yet

Be the first to review this book!