Artificial Intelligence in Medical Imaging
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PART I: INTRODUCTION
1 Introduction: Game changers in radiology
PART II: TECHNIQUES
2 The role of medical imaging computing, informatics and machine learning in healthcare
2 History and evolution of A.I. in medical imaging
3 Deep Learning and Neural Networks in imaging: basic principles
PART III DEVELOPMENT of AI APPLICATIONS
4 Imaging biomarkers
5 How to develop A.I. applications
6 Validation of A.I. applications
PART IV: BIG DATA IN RADIOLOGY
7 The value of enterprise imaging
8 Data mining in radiology
9 Image biobanks
10 The quest for medical images and data
11 Clearance of medical images and data
12 Legal and ethical issues in AI
PART V: CLINICAL USE OF A.I. IN RADIOLOGY
13 Pulmonary diseases
14 Cardiac diseases
15 Breast cancer
16 Neurological diseases
PART VI: IMPACT of A.I. on RADIOLOGY
17 Applications of A.I. beyond image analysis
18 Value of structured reporting for A.I.
19 The role of A.I. for clinical trials
20 Market and economy of A.I.: evolution
21 The role of an A.I. ecosystem for radiology
22 Advantages and risks of A.I. for radiologists
23 Re-thinking radiology
| Autor: | Ranschaert, Erik R. |
| Nakladatel: | Springer, Berlin |
| Rok vydání: | 2018 |
| Jazyk : | Angličtina |
| Vazba: | Hardback |
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