Dublin, Dec. 04, 2020 (GLOBE NEWSWIRE) -- The "Deep Learning Market: Focus on Medical Image Processing, 2020-2030" report has been added to ResearchAndMarkets.com's offering.

The 'Deep Learning Market: Focus on Medical Image Processing, 2020-2030' report features an extensive study on the current market landscape offering an informed opinion on the likely adoption of such solutions over the next decade. The study presents an in-depth analysis, highlighting the capabilities of various stakeholders engaged in this domain.

One of the key objectives of this report was to estimate the existing market size and the future growth potential within the deep learning market (medical image processing segment), such as global radiology spending across countries, number of radiologists employed across different regions of globe, annual salary of radiologists, rate of adoption of deep learning-based solutions, we have developed informed estimates on the financial evolution of the market, over the period 2020-2030.

The report also provides details on the likely distribution of the current and forecasted opportunity across [A] application area (lung infections/respiratory disorders, brain injuries/disorders, lung cancer, cardiac conditions/cardiovascular disorders, bone deformities/orthopedic disorders, breast cancer and others), [B] type of image processed (X-ray, MRI, CT, ultrasound) and [C] region (North America, Europe and Asia Pacific/Rest of the World).

In order to account for future uncertainties and to add robustness to our forecast model, we have provided three scenarios, namely conservative, base and optimistic scenarios, representing different tracks of the industry's growth.

The report features detailed transcripts of interviews held with the following individuals (in alphabetical order):

Key Topics Covered:

1. PREFACE
1.1. Scope of the Report
1.2. Research Methodology
1.3. Chapter Outlines

2. EXECUTIVE SUMMARY

3. INTRODUCTION
3.1. Humans, Machines and Intelligence
3.2. The Science of Learning
3.3. Artificial Intelligence
3.4. The Big Data Revolution
3.5. Applications of Deep Learning in Healthcare

4. CASE STUDY: IBM WATSON VERSUS GOOGLE DEEPMIND
4.1. Chapter Overview
4.2. International Business Machines (IBM)
4.3. Google
4.4. IBM versus Google: Artificial Intelligence-related Acquisitions
4.5. IBM versus Google: Healthcare Focused Partnerships and Collaborations
4.6. IBM versus Google: Primary Concerns and Future Outlook

5. MARKET OVERVIEW
5.1. Chapter Overview
5.2. Deep Learning in Medical Image Processing: Overall Market Landscape
5.3. Deep Learning in Medical Image Processing: Information on Key Characteristics
5.4. Deep Learning in Medical Image Processing: List of Companies

6. COMPANY PROFILES
6.1. Chapter Overview
6.2. Artelus
6.3. Arterys
6.4. Butterfly Network
6.5. ContextVision
6.6. Enlitic
6.7. Echonous
6.8. GE Healthcare
6.9. InferVision
6.10. VUNO

7. PARTNERSHIPS AND COLLABORATIONS
7.1. Chapter Overview
7.2. Partnership Models
7.3. Deep Learning in Medical Image Processing: List of Partnerships and Collaborations
7.4. Concluding Remarks

8. FUNDING AND INVESTMENT ANALYSIS
8.1. Chapter Overview
8.2. Types of Funding
8.3. Deep Learning in Medical Image Processing: Recent Funding Instances

9. COMPANY VALUATION ANALYSIS
9.1. Chapter Overview
9.2. Methodology
9.3. Categorization by Parameters

10. CASE STUDY: ANALYSIS OF DEEP LEARNING-BASED CLINICAL TRIALS REGISTERED IN THE US
10.1. Chapter Overview
10.2. Scope and Methodology
10.3 Clinical Trial Analysis

11. PATENT ANALYSIS
11.1. Chapter Overview
11.2. Scope and Methodology
11.3. Deep Learning and Medical Image Processing: Patent Analysis
11.4. Patent Valuation Analysis

12. COST SAVING ANALYSIS
12.1. Chapter Overview
12.2. Key Assumptions and Methodology
12.3. Overall Cost Saving Potential of Deep Learning in Medical Image Processing Solutions, 2020-2030
12.4. X-Ray Images
12.5. MRI Images
12.6. CT Images
12.7. Ultrasound Images
12.8. Concluding Remarks: Cost Saving Scenarios

13. MARKET FORECAST
13.1. Chapter Overview
13.2 Forecast Methodology and Key Assumptions
13.3 Overall Deep Learning in Medical Image Processing Market
13.3 Deep Learning in Medical Image Processing Market: Distribution by Application Area
13.4 Deep Learning in Medical Image Processing Market: Distribution by Type of Image Processed
13.5 Deep Learning in Medical Image Processing Market: Distribution by Key Geographical Regions
13.6 Concluding Remarks

14. DEEP LEARNING IN HEALTHCARE: EXPERT INSIGHTS
14.1. Chapter Overview
14.2. Industry Experts
14.3. University and Hospital Experts
14.4. Other Expert Opinions

15. INTERVIEW TRANSCRIPTS
15.1 Chapter Overview
15.2. Advenio Technosys
15.3. Arterys
15.4. Arya.ai
15.5. AlgoSurg
15.6. ContextVision

16. IMPACT OF COVID-19 OUTBREAK ON DEEP LEARNING MARKET DYNAMICS
16.1. Chapter Overview
16.2. Evaluation of Impact of COVID-19 Pandemic
16.3. Response Strategies: A Perspective

17. CONCLUSION

18. APPENDIX 1: TABULATED DATA

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/q4vt1o

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