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대한민국 원환율 (2021-01-26)
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Artificial Intelligence in Medical Imaging(Hardcover)
Artificial Intelligence i
       판매가 : 200,000180,000
       적립금 : 3,600
       저   자 : Ranschaert
       역   자 :
       출판사 : Springer
    ISBN(13) : 9783319948775
       발행일 : 2019-02-28  /   1판   /   373 페이지
       상품코드 : 26673
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This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI)
within
healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the
impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology,
such as deep learning technology, the technological evolution of AI in computing science and medical image
computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections
address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and
issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then
outlined
for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section
focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training.
Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical
physicists,
IT specialists, and imaging informatics professionals.




Part I Introduction
 1. Introduction: Game Changers in Radiology

Part II Technology: Getting Started
 2. The Role of Medical Image Computing and Machine Learning in Healthcare
 3. A Deeper Understanding of Deep Learning
 4. Deep Learning and Machine Learning in Imaging: Basic Principles

Part III Technology: Developing A.I. Applications
 5. How to Develop Artificial Intelligence Applications
 6. A Standardised Approach for Preparing Imaging Data for Machine Learning Tasks in Radiology
 7. The Value of Structured Reporting for AI
 8. Artificial Intelligence in Medicine: Validation and Study Design

Part IV Big Data in Medicine
 9. Enterprise Imaging
 10. Imaging Biomarkers and Imaging Biobanks

Part V Practical Use Cases of A.I. in Radiology
 11. Applications of AI Beyond Image Interpretation
 12. Artificial Intelligence and Computer-Assisted Evaluation of Chest Pathology
 13. Cardiovascular Diseases
 14. Deep Learning in Breast Cancer Screening
 15. Neurological Diseases
 16. The Role of AI in Clinical Trials

Part VI Quality, Regulatory and Ethical Issues
 17. Quality and Curation of Medical Images and Data
 18. Does Future Society Need Legal Personhood for Robots and AI?
 19. The Role of an Artificial Intelligence Ecosystem in Radiology
 20. Advantages, Challenges, and Risks of Artificial Intelligence for Radiologists
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