The Radiology AI Handbook
1. Cover image - p. c 2. Title page - p. iii 3. Copyright - p. iv 4. Contributors - p. v 5. Preface - p. viii 6. Acknowledgments - p. ix 7. Table of Contents - p. x 8. PART I Background - p. 1 9. Chapter 1 AI in Radiology—Past and Present - p. 3 10. Chapter 2 AI in Radiology—Future - p. 9 11. Chapter 3 Technical Principles - p. 19 12. PART II Interpretive Applications - p. 29 13. Chapter 4 Interpretive Applications of Artificial Intelligence in Breast Radiology - p. 31 14. Chapter 5 Artificial Intelligence in Cardiovascular Imaging - p. 45 15. Chapter 6 Interpretive Applications: Chest - p. 51 16. Chapter 7 ArtificiaI Intelligence in Emergency Radiology - p. 59 17. Chapter 8 Artificial Intelligence in Gastrointestinal Imaging - p. 63 18. Chapter 9 Genitourinary - p. 71 19. Chapter 10 ArtificiaI Intelligence In Head and Neck Radiology: Current Innovations, Challenges, and Future Directions - p. 77 20. Chapter 11 Interpretive Applications: Musculoskeletal - p. 85 21. Chapter 12 Neuroradiology - p. 93 22. Chapter 13 Interpretive Applications of Artificial Intelligence in Interventional Radiology - p. 101 23. Chapter 14 Artificial Intelligence in Nuclear Radiology: Unlocking the Potential for Enhanced Patient - p. 111 24. PART III Noninterpretive Applications - p. 125 25. Chapter 15 Patient Facing Noninterpretive Artificial Intelligence Applications - p. 127 26. Chapter 16 Navigating the Radiologic Technologist’s Landscape: Current Innovations and Future Directions of Artificial Intelligence in Radiology - p. 133 27. Chapter 17 Business-Facing Approaches - p. 145 28. Chapter 18 Non-interpretive Application of Artificial Intelligence in Radiology: Population Health - p. 153 29. PART IV Develop Your Application - p. 161 30. Chapter 19 Data Curation - p. 163 31. Chapter 20 Artificial Intelligence Network Training and Validation in Radiology: Recent Developments and Real-World Examples - p. 187 32. Chapter 21 Regulatory Considerations for Radiology Artificial Intelligence/Machine Learning Devices - p. 197 33. PART V Case Studies - p. 209 34. Chapter 22 Response to COVID With Artificial Intelligence–Assisted Radiologic Diagnosis - p. 211 35. Chapter 23 Arterys Artificial Intelligence: Inception, Development, Growth - p. 219 36. Chapter 24 Viz.ai—Pioneering Artificial Intelligence in Healthcare - p. 227 37. Index - p. 241
The Radiology AI Handbook
1. Cover image - p. c 2. Title page - p. iii 3. Copyright - p. iv 4. Contributors - p. v 5. Preface - p. viii 6. Acknowledgments - p. ix 7. Table of Contents - p. x 8. PART I Background - p. 1 9. Chapter 1 AI in Radiology—Past and Present - p. 3 10. Chapter 2 AI in Radiology—Future - p. 9 11. Chapter 3 Technical Principles - p. 19 12. PART II Interpretive Applications - p. 29 13. Chapter 4 Interpretive Applications of Artificial Intelligence in Breast Radiology - p. 31 14. Chapter 5 Artificial Intelligence in Cardiovascular Imaging - p. 45 15. Chapter 6 Interpretive Applications: Chest - p. 51 16. Chapter 7 ArtificiaI Intelligence in Emergency Radiology - p. 59 17. Chapter 8 Artificial Intelligence in Gastrointestinal Imaging - p. 63 18. Chapter 9 Genitourinary - p. 71 19. Chapter 10 ArtificiaI Intelligence In Head and Neck Radiology: Current Innovations, Challenges, and Future Directions - p. 77 20. Chapter 11 Interpretive Applications: Musculoskeletal - p. 85 21. Chapter 12 Neuroradiology - p. 93 22. Chapter 13 Interpretive Applications of Artificial Intelligence in Interventional Radiology - p. 101 23. Chapter 14 Artificial Intelligence in Nuclear Radiology: Unlocking the Potential for Enhanced Patient - p. 111 24. PART III Noninterpretive Applications - p. 125 25. Chapter 15 Patient Facing Noninterpretive Artificial Intelligence Applications - p. 127 26. Chapter 16 Navigating the Radiologic Technologist’s Landscape: Current Innovations and Future Directions of Artificial Intelligence in Radiology - p. 133 27. Chapter 17 Business-Facing Approaches - p. 145 28. Chapter 18 Non-interpretive Application of Artificial Intelligence in Radiology: Population Health - p. 153 29. PART IV Develop Your Application - p. 161 30. Chapter 19 Data Curation - p. 163 31. Chapter 20 Artificial Intelligence Network Training and Validation in Radiology: Recent Developments and Real-World Examples - p. 187 32. Chapter 21 Regulatory Considerations for Radiology Artificial Intelligence/Machine Learning Devices - p. 197 33. PART V Case Studies - p. 209 34. Chapter 22 Response to COVID With Artificial Intelligence–Assisted Radiologic Diagnosis - p. 211 35. Chapter 23 Arterys Artificial Intelligence: Inception, Development, Growth - p. 219 36. Chapter 24 Viz.ai—Pioneering Artificial Intelligence in Healthcare - p. 227 37. Index - p. 241
