Overview
- Provides an understanding of the interfaces between the model and other factors, and of clinical applications
- Offers comprehensive, in-depth understanding of deep learning-based medical image analysis
- Presents mathematical formulation and analysis that can be dealt with systematically and quantitatively
Part of the book series: Mathematics in Industry (MATHINDUSTRY, volume 40)
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Table of contents (7 chapters)
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Front Matter
Keywords
About this book
AI advancements of medical imaging not only address existing unsolved problems but also present new and complex challenges. Solutions to these challenges can improve image quality and reveal new information currently obscured by noise, artifacts, or other signals. Holistic insight is the key to solving these challenges. Such insight may lead to a creative solution only when it is based on a thorough understanding of existing methods and unmet demands.
This book focuses on advanced topics in medical imagingmodalities, including CT and ultrasound, with the aim of providing practical applications in the healthcare industry. It strikes a balance between mathematical theory, numerical practice, and clinical applications, offering comprehensive coverage from basic to advanced levels of mathematical theories, deep learning techniques, and algorithm implementation details. Moreover, it provides in-depth insights into the latest advancements in dental cone-beam CT, fetal ultrasound, and bioimpedance, making it an essential resource for professionals seeking to stay up-to-date with the latest developments in the field of medical imaging.
Editors and Affiliations
About the editor
Bibliographic Information
Book Title: Deep Learning and Medical Applications
Editors: Jin Keun Seo
Series Title: Mathematics in Industry
DOI: https://doi.org/10.1007/978-981-99-1839-3
Publisher: Springer Singapore
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023
Hardcover ISBN: 978-981-99-1838-6Published: 16 June 2023
Softcover ISBN: 978-981-99-1841-6Due: 17 July 2023
eBook ISBN: 978-981-99-1839-3Published: 15 June 2023
Series ISSN: 1612-3956
Series E-ISSN: 2198-3283
Edition Number: 1
Number of Pages: XV, 339
Number of Illustrations: 20 b/w illustrations, 216 illustrations in colour
Topics: Mathematical Modeling and Industrial Mathematics, Partial Differential Equations, Mathematical Applications in the Physical Sciences