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).
The market applications are segmented into image analysis (which is the most dominant area), cognitive applications, machine intelligence, and research and development services around AI solutions for providers and other business-to-business vendors.
According to research, the market will grow with double-digit rates year-on-year, with image analysis being the predominant segment, but machine intelligence will become 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, investments in the field are gradually slowing down, but it may pick up again.
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 Topics Covered
1. EXECUTIVE DASHBOARD
Purpose of this Experiential Study
5 Step Process to Transformational Growth
Strategic Imperatives for AI for Medical Imaging Market
2. GROWTH ENVIRONMENT - INTRODUCTION TO ARTIFICIAL INTELLIGENCE
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
3. GROWTH ENVIRONMENT - MEDICAL IMAGING AI APPLICATIONS
Medical Imaging AI Market Segmentation
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
4. GROWTH ENVIRONMENT - MARKET FORECASTS
Segment Scope for Revenue Forecasts
Types of Revenue Generators in AI for Medical Imaging Market
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