Artificial Intelligence in Medical Ultrasound
- 1st Edition - June 1, 2027
- Latest edition
- Editor: Zhuhuang Zhou
- Language: English
Artificial Intelligence in Medical Ultrasound is an authoritative reference that explores the integration of advanced AI methodologies within the field of ultrasound imagin… Read more
Description
Description
Artificial Intelligence in Medical Ultrasound is an authoritative reference that explores the integration of advanced AI methodologies within the field of ultrasound imaging. The book addresses the critical need for specialized knowledge on AI-driven ultrasound techniques, which are rapidly transforming diagnostic and therapeutic practices. It covers a broad spectrum of topics, including AI-assisted image processing, quantitative ultrasound, multimodal deep learning, and emerging models such as generative adversarial networks and physics-informed neural networks. The detailed table of contents delineates chapters authored by leading international experts, providing both foundational principles and cutting-edge research developments. The content is designed to serve researchers, engineers, and clinicians seeking to understand, develop, and deploy AI models in ultrasound applications. Its comprehensive scope ensures that readers will gain a deep understanding of the latest innovations, practical applications, and future directions in the field. This reference aims to facilitate the adoption of AI techniques in clinical settings, improve diagnostic accuracy, and accelerate the development of next-generation ultrasound technologies. Overall, it is an essential resource for advancing research, guiding clinical practice, and fostering innovation in medical ultrasound with artificial intelligence.
Key features
Key features
- Presents cutting-edge AI techniques in ultrasound imaging and analysis
- Demonstrates clinical and pre-clinical applications of AI models
- Explores emerging AI methods like deep learning, reinforcement learning, and large language models
- Highlights multimodal and physics-informed neural network approaches
- Provides comprehensive coverage of AI-driven ultrasound technologies
Readership
Readership
Ultrasound scientists, researchers, radiologists, and sonographers
Table of contents
Table of contents
1. Artificial intelligence-assisted ultrasound scanning
2. Artificial intelligence in ultrasound beamforming
3. Deep learning in ultrasound image segmentation
4. Artificial intelligence in quantitative ultrasound imaging
5. Reinforcement learning in ultrasound imaging
6. Explainable artificial intelligence in ultrasound image analysis
7. Multimodal deep learning in ultrasound image analysis
8. Generative adversarial networks in virtual ultrasound elastography
9. Physics-informed neural networks in ultrasound wave propagation
10. Deep learning in ultrasound localization microscopy
11. Large language models in ultrasound
12. Artificial intelligence in superficial organs ultrasound
13. Artificial intelligence in fetal ultrasound
14. Artificial intelligence in abdominal organs ultrasound
15. Artificial intelligence in transthoracic and transesophageal echocardiography
2. Artificial intelligence in ultrasound beamforming
3. Deep learning in ultrasound image segmentation
4. Artificial intelligence in quantitative ultrasound imaging
5. Reinforcement learning in ultrasound imaging
6. Explainable artificial intelligence in ultrasound image analysis
7. Multimodal deep learning in ultrasound image analysis
8. Generative adversarial networks in virtual ultrasound elastography
9. Physics-informed neural networks in ultrasound wave propagation
10. Deep learning in ultrasound localization microscopy
11. Large language models in ultrasound
12. Artificial intelligence in superficial organs ultrasound
13. Artificial intelligence in fetal ultrasound
14. Artificial intelligence in abdominal organs ultrasound
15. Artificial intelligence in transthoracic and transesophageal echocardiography
Product details
Product details
- Edition: 1
- Latest edition
- Published: June 1, 2027
- Language: English
About the editor
About the editor
Zhuhuang Zhou
Editor
Zhuhuang Zhou is an associate professor of biomedical engineering, Beijing University of Technology, China. His research interests include biomedical ultrasonics, quantitative ultrasound for tissue characterization, ultrasound propagation in tissues, acoustic cavitation & bubble dynamics, biomedical signal/image processing, and artificial intelligence in medicine. He is an editorial board member of Scientific Reports (2024-) and Diagnostics (2023-) and has received the Springer Nature Editor of Distinction Awards in 2025. He has published 83 journal articles, co-edited a special issue in Frontiers in Physiology entitled, “Recent advances in artificial intelligence-empowered ultrasound tissue characterization for disease diagnosis, intervention guidance, and therapy monitoring,” and is editing a special issue in Diagnostics entitled “Deep learning techniques for medical image analysis.” He has served as a reviewer for over 50 journals and received the IOP “Trusted Reviewer” and “Outstanding Reviewer” awards in 2023 and 2019, respectively.
Affiliations and expertise
Associate Professor, Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China