Global Artificial Intelligence in the Medical Imaging Market 2020 Segmentation, Demand, Growth, Trend, Opportunity and Forecast to 2026

Wiseguyreports.Com Adds “Artificial Intelligence in the Medical Imaging - Market Demand, Growth, Opportunities, Manufacturers and Analysis of Top Key Players to 2026” To Its Research Database.

Updated Research Report of Artificial Intelligence in the Medical Imaging Market 2020-2026:


Wiseguyreports.Com Adds “Artificial Intelligence in the Medical Imaging - Market Demand, Growth, Opportunities, Manufacturers and Analysis of Top Key Players to 2026” To Its Research Database.


Artificial Intelligence (AI) for medical imaging is a reality now. While image analysis applications are the most advanced, adopted, and well-known, there are several other use cases which are probably not as well-known or thought of. Applications across the imaging workflow, beginning with the ordering of images by a physician, scheduling of the scans, image acquisitions, assignment of the studies, viewing those studies, analyzing (or the aforementioned image analysis example), interpreting, deciding, reporting, and follow-up can all benefit from using AI. However, all these applications lie in the clinical side of medical imaging; AI can have preclinical applications as well that aim to serve the medical research aspects of healthcare (imaging biomarker validations or patient-matching for clinical trials, for example).

We segment the market applications into image analysis (which is the most dominant area), cognitive applications (which deal with non-pixel data-related AI), machine intelligence (or ‘smart’ medical imaging equipment), and research and development services around AI solutions for providers and other business-to-business vendors. We believe the market will grow with double-digit rates year-on-year, with image analysis being the predominant segment, but we will also see machine intelligence becoming the second largest segment by the end of this forecast period.

Considering the types of applications AI has within the medical imaging industry, it is without a doubt that it will impact all aspects of the medical imaging services industry, which includes diagnostic and imaging equipment, imaging informatics as well as professional services sectors. These sectors will reap a significant return on investments (ROI) by implementing AI by productivity and quality gains. Despite this, we find the investments in the field to be gradually slowing down, but we also feel it may pick up again.

Market segment by Type, the product can be split into
Digital Pathology

Market segment by Application, split into
Diagnostic Centers


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Based on regional and country-level analysis, the Artificial Intelligence in the Medical Imaging market has been segmented as follows:
North America
United States
Rest of Europe
South Korea
Southeast Asia
Rest of Asia-Pacific
Latin America
Middle East & Africa
Saudi Arabia
Rest of Middle East & Africa

In the competitive analysis section of the report, leading as well as prominent players of the global Artificial Intelligence in the Medical Imaging market are broadly studied on the basis of key factors. The report offers comprehensive analysis and accurate statistics on revenue by the player for the period 2015-2020. It also offers detailed analysis supported by reliable statistics on price and revenue (global level) by player for the period 2015-2020.

The key players covered in this study
NVIDIA Corporation
GE Healthcare
Agfa Healthcare
Butterfly Network, Inc.
EchoNous, Inc.
Enlitic, Inc.


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Major Key Points in Table of Content

1 Study Coverage

2 Executive Summary

3 Global Artificial Intelligence in the Medical Imaging Competitor Landscape by Players

4 Market Size by Type (2015-2026)

5 Market Size by Application (2015-2026)

6 North America

7 Europe

8 Asia Pacific

9 Latin America

10 Middle East and Africa

11 Company Profiles

12 Future Forecast by Regions (Countries) (2021-2026)

13 Market Opportunities, Challenges, Risks and Influences Factors Analysis

14 Value Chain and Sales Channels Analysis

15 Research Findings and Conclusion





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