Growth Opportunities in the Global Medical Imaging Artificial Intelligence Market, Forecast to 2022
Growth Opportunities in the Global Medical Imaging Artificial Intelligence Market, Forecast to 2022
Emerging Use Cases, Revenue, and Industry Savings Potential
30-Oct-2018
North America
Description
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.
Research Scope
This study analyzes over 135 global companies active in the AI for medical imaging space and mapping their solutions along the application segments described above. It also identifies some of the leading global providers involved in AI research for medical imaging. Additionally, it summarizes initiatives by larger tech companies, including the GAFAM companies. Overall, it has several analyses around the startup landscape, regulatory approvals, kinds of investments in this industry and their expected ROI, adoption in the industry, revenue forecasts, and also growth opportunities.
Key Issues Addressed
- What is artificial intelligence, and how does it play a role in healthcare and specifically in medical imaging? What are the various use cases for AI in medical imaging, across the imaging workflow? Which are the representative companies that either have or can support AI solutions for each of these areas?
- What is the estimated market or revenue size for AI in medical imaging, and what would be the expected growth until 2022? How does that compare with medical imaging services industry’s savings resulting from investing and implementing AI solutions?
- What does the competitive landscape look like?
- By when will AI be adopted in the mainstream in medical imaging?
- What are the top 10 predictions for this market, and what are the top 10 growth opportunities in this space?
RESEARCH: INFOGRAPHIC
This infographic presents a brief overview of the research, and highlights the key topics discussed in it.Click image to view it in full size
Table of Contents
Purpose of this Experiential Study
5 Step Process to Transformational Growth
Strategic Imperatives for AI for Medical Imaging Market
Market Definitions
Recognizing AI Potential
Discerning AI Applications
Understanding Available AI Techniques
How to Categorize AI Systems in Healthcare
Drivers and Restraints for AI in Medical Imaging
Medical Imaging AI Market Segmentation
Medical Imaging AI Market Segmentation (continued)
Preclinical Applications for Medical Imaging AI
Medical Imaging AI Applications Across Imaging Workflow
Maturity of AI Applications Along the Clinical Imaging Workflow
Use Cases and Applications at Ordering Stage
Use Cases and Applications at Scheduling Stage
Use Cases and Applications at Acquisition Stage
Use Cases and Applications at Assigning Stage
Use Cases and Applications at Viewing Stage
Use Cases and Applications at Analysis Stage
Use Cases and Applications at Interpretation Stage
Use Cases and Applications at Decision Stage
Use Cases and Applications at Reporting Stage
Use Cases and Applications at Follow-up Stage
Segment Scope for Revenue Forecasts
Types of Revenue Generators in AI for Medical Imaging Market
Revenue Forecast
Revenue Forecast Discussion
Percent Revenue Forecast by Segment
Percent Revenue Forecast Discussion by Segment
Revenue Forecast by Segment
Revenue Forecast Discussion—Image Analysis
Revenue Forecast Discussion—Machine Intelligence
Revenue Forecast Discussion—Cognitive Computing
Revenue Forecast Discussion—R&D Services
AI’s Impact on Medical Imaging Services Market
Medical Imaging AI Savings Opportunity
Provider Investment and Savings from Medical Imaging AI Applications
Savings Generated by Medical Imaging AI Solutions
Categories of Industry Savings
Productivity Vs. Quality Gains
Assessing Medical Imaging Industry Savings Using AI
Medical Imaging AI Applications Adoption Scenarios
Adoption of Medical Imaging AI Solutions—Discussion
Medical Imaging AI Investments
Medical Imaging AI Investments (continued)
Global Targets for Medical Imaging AI Investments
Regional Analysis of Startup Investment
Regional Analysis of Startup Investment (continued)
Regional Analysis of Startup Investment (continued)
Regional Analysis of Startup Landscape
Investments Vs. Revenues
Investments Vs. Revenues (continued)
Investments Vs. Revenues (continued)
Investments Vs. Revenues (continued)
Medical Imaging AI—Technology Stack
Global Provider Organizations Leading Charge in Medical Imaging AI R&D
Universe of Medical Image Analysis AI Companies
Universe of Medical Image Analysis AI Companies (continued)
The GAFAM of Medical Imaging AI—TAFMIGA
Rise of New Medical Imaging AI Applications During 2009–2022
Rise of New Medical Imaging AI Applications During 2009–2022 (continued)
Macro to Micro Visioning
Trends/Factors Impacting the Medical Imaging AI Market
Top 10 Predictions for AI in Medical Imaging Market
Top 10 Predictions for AI in Medical Imaging Market (continued)
Levers for Growth
Growth Opportunity 1—Acceleration and Automation of Manual Image Analysis Tasks
Growth Opportunity 1—Acceleration and Automation of Manual Image Analysis Tasks (continued)
Potential of Growth Opportunity 1—Acceleration and Automation of Manual Image Analysis Tasks
Economic Model Supporting Growth Opportunity 1—Acceleration and Automation of Manual Image Analysis Tasks
Economic Model Supporting Growth Opportunity 1—Acceleration and Automation of Manual Image Analysis Tasks (continued)
Growth Opportunity 2—Augmentation of Current Image Analysis Practices
Growth Opportunity 2—Augmentation of Current Image Analysis Practices (continued)
Potential of Growth Opportunity 2—Augmentation of Current Image Analysis Practices
Growth Opportunity 3—On-demand Inferencing of Cloud-based SaaS Apps
Growth Opportunity 3—On-demand Inferencing of Cloud-based SaaS Apps (continued)
Growth Opportunity 3—On-demand Inferencing of Cloud-based SaaS Apps (continued)
Growth Opportunity 4—R&D Services to the AI Development Community
Growth Opportunity 4—R&D Services to the AI Development Community (continued)
Illustration of Growth Opportunity 4—R&D Services to the AI Development Community
Illustration of Growth Opportunity 4—R&D Services to the AI Development Community (continued)
Growth Opportunity 5—Cognitive Medical Imaging Workflow Tools
Growth Opportunity 5—Cognitive Medical Imaging Workflow Tools (continued)
Growth Opportunity 5—Cognitive Medical Imaging Workflow Tools (continued)
Growth Opportunity 6—Image-guided Procedures and Radiotherapy Treatment Planning
Growth Opportunity 6—Image-guided Procedures and Radiotherapy Treatment Planning (continued)
Growth Opportunity 6—Image-guided Procedures and Radiotherapy Treatment Planning (continued)
Growth Opportunity 7—Deep Learning-based Image Reconstruction
Growth Opportunity 7—Deep Learning-based Image Reconstruction (continued)
Growth Opportunity 7—Deep Learning-based Image Reconstruction (continued)
Advances in Growth Opportunity 7—Deep Learning-based Image Reconstruction in MRI
Growth Opportunity 8—Intelligent Medical Imaging Machines
Growth Opportunity 8—Intelligent Medical Imaging Machines (continued)
Growth Opportunity 8—Intelligent Medical Imaging Machines (continued)
Growth Opportunity 9—AI Applied at the Edge
Growth Opportunity 9—AI Applied at the Edge (continued)
Growth Opportunity 9—AI Applied at the Edge (continued)
Growth Opportunity 10—AI as a Contributor of Precision Health
Growth Opportunity 10—AI as a Contributor of Precision Health (continued)
Growth Opportunity 10—AI as a Contributor of Precision Health (continued)
Growth Opportunity 10—AI as a Contributor of Precision Health(continued)
Summarized Growth Opportunities
Identifying Your Company’s Growth Zone
Growth Opportunities 1-10—Vision and Strategy
Growth Opportunities Matrix
Growth Strategies for Your Company
Prioritized Opportunities through Implementation
Legal Disclaimer
Abbreviations and Acronyms Used
AI Development Engagement Models
AI Development Engagement Models (continued)
List of Exhibits
List of Exhibits (continued)
List of Exhibits (continued)
Popular Topics
Research Scope
This study an
No Index | No |
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Podcast | No |
Author | Harpreet Singh Buttar |
Industries | Healthcare |
WIP Number | MD1C-01-00-00-00 |
Is Prebook | No |
GPS Codes | 9600-B1,9AD7-B1,9566-B1,9570-B1,99BE-B1,9B07-C1,9614-B1 |