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Artificial Intelligence in Medical Imaging: Opportunities, Applications and Risks


Artificial Intelligence in Medical Imaging: Opportunities, Applications and Risks
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Beschreibung

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

Eigenschaften

Breite: 178
Gewicht: 1062 g
Höhe: 263
Länge: 23
Seiten: 373
Sprachen: Englisch
Autor: Erik R. Ranschaert, Paul R. Algra, Sergey Morozov

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