Emerging Use Cases, Revenue, and Industry Savings Potential
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?
