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

RELEASE DATE
30-Oct-2018
REGION
North America
Research Code: MD1C-01-00-00-00
SKU: HC03099-NA-MT_22490
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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)

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.--BEGIN PROMO--

Research Scope

This study an

More Information
No Index No
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