Artificial Intelligence Ai In Medical Imaging Market
Artificial Intelligence (AI) in Medical Imaging Market Forecasts to 2032 - Global Analysis By Imaging Modality (X-Ray, Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, Positron Emission Tomography (PET), Mammography and Other Imaging Modalities), AI Type (Machine Learning, Deep Learning, Natural Language Processing (NLP) and Computer Vision), Clinical Area, Deployment Model, Component, Application, End User and By Geography
|
Years Covered |
2024-2032 |
|
Estimated Year Value (2025) |
US $1.97 BN |
|
Projected Year Value (2032) |
US $8.81 BN |
|
CAGR (2025 - 2032) |
23.8% |
|
Regions Covered |
North America, Europe, Asia Pacific, South America, and Middle East & Africa |
|
Countries Covered |
US, Canada, Mexico, Germany, UK, Italy, France, Spain, Japan, China, India, Australia, New Zealand, South Korea, Rest of Asia Pacific, South America, Argentina, Brazil, Chile, Middle East & Africa, Saudi Arabia, UAE, Qatar, and South Africa |
|
Largest Market |
Asia Pacific |
|
Highest Growing Market |
North America |
According to Stratistics MRC, the Global Artificial Intelligence (AI) in Medical Imaging Market is accounted for $1.97 billion in 2025 and is expected to reach $8.81 billion by 2032 growing at a CAGR of 23.8% during the forecast period. Artificial Intelligence (AI) in medical imaging involves leveraging advanced computational models to evaluate and interpret visual healthcare data. By applying machine learning and deep learning techniques, AI enhances the precision of image-based diagnostics while minimizing human oversight. It enables automated analysis of modalities like MRI, CT scans, and X-rays, facilitating early disease detection and diagnostic consistency. The technology contributes to improved image resolution, supports predictive insights, and streamlines radiology workflows to assist clinicians in making more informed decisions.
According to The Lancet Digital Health, AI systems achieved diagnostic accuracy comparable to expert radiologists, with pooled sensitivity of 87% and specificity of 92% across over 31,000 medical imaging cases. According to the same meta-analysis, AI also significantly reduced image interpretation time.
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Market Dynamics:
Driver:
Rising burden of chronic diseases and demand for early diagnosis
The increasing prevalence of chronic ailments such as cardiovascular conditions, cancer, and neurological disorders has heightened the need for prompt and accurate diagnostic tools. AI-powered medical imaging enhances the detection of anomalies at early stages, allowing for timely intervention and improved treatment outcomes. Healthcare providers are increasingly integrating AI to augment radiological assessments and streamline diagnostic workflows. Moreover AI’s ability to analyze complex imaging data swiftly and precisely makes it vital in addressing long-term care challenges.
Restraint:
Data privacy, security concerns, and fragmented data governance
As AI systems rely heavily on vast medical datasets, safeguarding patient privacy has become a pressing issue. The use of cloud-based analytics and third-party platforms introduces risks related to unauthorized access and data breaches. Moreover, inconsistent governance frameworks across institutions complicate data sharing and standardization efforts. Ensuring compliance with international data protection laws adds complexity, especially when deploying AI solutions across different jurisdictions. These concerns collectively restrict the pace of AI adoption in imaging diagnostics.
Opportunity:
Expansion into new therapeutic areas and predictive analytics
AI is evolving from supporting diagnostics to enabling proactive disease management through predictive modeling. Its capabilities are extending to areas such as oncology, cardiology, and neuroimaging, facilitating deeper insights into disease progression. By recognizing subtle imaging biomarkers, AI assists clinicians in forecasting potential health risks and refining treatment plans. This broadening scope presents opportunities for developers and healthcare institutions to innovate beyond traditional imaging use cases.
Threat:
Over-reliance on AI and deskilling of radiologists
Automated systems may cause skill erosion, especially in routine diagnostic tasks. Furthermore, incorrect AI outputs due to biased or poor-quality training data can mislead clinical decisions. A lack of human oversight might increase risks in complex cases requiring nuanced judgment. The shift toward automation necessitates upskilling medical professionals to effectively collaborate with AI tools. Maintaining a balance between technology support and human expertise is essential to avoid undermining diagnostic accuracy and professional competency.
Covid-19 Impact:
The COVID-19 crisis accelerated the integration of AI in medical imaging, especially for assessing lung complications and monitoring disease progression. Lockdowns and hospital overcrowding emphasized the need for remote diagnostic solutions and automated analysis. Despite initial resource constraints, the pandemic catalyzed innovation in AI-driven imaging platforms. It also fostered acceptance among clinicians of digital diagnostic tools for respiratory assessments. As the healthcare sector pivots toward digital resilience, AI in imaging is expected to become a cornerstone of post-pandemic diagnostics.
The computed tomography (CT) segment is expected to be the largest during the forecast period
The computed tomography (CT) segment is expected to account for the largest market share during the forecast period due to its versatility in capturing high-resolution anatomical details across multiple specialties. With the integration of AI, CT scan interpretation has become faster and more accurate, enhancing diagnostic confidence. The modality is widely used for detecting tumors, vascular diseases, and trauma-related injuries. AI algorithms in CT imaging support automated segmentation, anomaly detection, and report generation.
The quantitative imaging & biomarkers segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the quantitative imaging & biomarkers segment is predicted to witness the highest growth rate because AI tools are now capable of extracting measurable indicators from imaging data that correlate with disease severity or response to treatment. These biomarkers support individualized patient monitoring and drug efficacy evaluation. Healthcare institutions are investing in platforms that integrate imaging biomarkers with genomic and clinical data for comprehensive analysis.
Region with largest share:
During the forecast period, the Asia Pacific region is expected to hold the largest market share owing to its expanding healthcare infrastructure and rapid technology adoption. Governments across countries like China, Japan, and India are promoting AI integration through policy support and public-private partnerships. Rising patient volumes and improving access to diagnostic services are contributing to regional growth. AI-driven medical imaging is being embraced to address disparities in radiologist availability and diagnostic accuracy.
Region with highest CAGR:
Over the forecast period, the North America region is anticipated to exhibit the highest CAGR fueled by robust R&D, established healthcare networks, and favorable regulations. The region hosts numerous AI startups and academic institutions focused on developing advanced imaging algorithms. AI’s utility in streamlining clinical workflows and addressing radiologist shortages is well recognized in the U.S. and Canada. Regulatory progress in AI-enabled diagnostics supports commercialization, positioning North America as a key accelerator of global market growth.
Key players in the market
Some of the key players in Artificial Intelligence (AI) in Medical Imaging Market include Aidoc, Arterys, Avicenna.AI, Canon Medical Systems Corporation, CureMetrix, Enlitic, GE HealthCare, HeartFlow Inc., IBM Watson Health, Infervision, Lunit Inc., Philips Healthcare, Qure.ai, RadNet, Riverain Technologies, ScreenPoint Medical, Siemens Healthineers, Therapixel and Zebra Medical Vision.
Key Developments:
In June 2025, Qure.ai launches AIRA AI?powered co?pilot at the World Health Assembly. The tool aims to reduce manual workload—freeing time for direct patient care responding to the WHO’s call for improved health equity.
In May 2025, GE HealthCare unveils enterprise imaging workflow efficiency solutions, introducing a suite of digital tools to optimize imaging operations and support enterprise-level deployments.
In January 2025, Aidoc announces strategic collaboration with AWS to enhance its CARE™ Foundation Model using Amazon Web Services’ cloud and engineering scale, aiming to deliver real-time clinical AI across multiple imaging modalities.
Imaging Modalities Covered:
• X-Ray
• Computed Tomography (CT)
• Magnetic Resonance Imaging (MRI)
• Ultrasound
• Positron Emission Tomography (PET)
• Mammography
• Other Imaging Modalities
AI Types Covered:
• Machine Learning
• Deep Learning
• Natural Language Processing (NLP)
• Computer Vision
Clinical Areas Covered:
• Radiology
• Cardiology
• Neurology
• Breast Screening/Breast Imaging
• Oncology
• Respiratory & Pulmonary
• Orthopedics
• Other Clinical Areas
Deployment Models Covered:
• On-Premise
• Cloud-based
• Hybrid
Components Covered:
• Software
• Hardware
• Services
Applications Covered:
• Image analysis & Interpretation
• Computer-Aided Diagnosis (CAD)
• Quantitative Imaging & Biomarkers
• Detection & Classification
• Workflow Optimization & Triage
• Other Applications
End Users Covered:
• Hospitals
• Diagnostic Imaging Centers
• Research Laboratories & Academic Institutions
• Pharmaceutical & Biotechnology Companies
• Other End Users
Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
o Benchmarking of key players based on product portfolio, geographical presence, and strategic alliance
Table of Contents
1 Executive Summary
2 Preface
2.1 Abstract
2.2 Stake Holders
2.3 Research Scope
2.4 Research Methodology
2.4.1 Data Mining
2.4.2 Data Analysis
2.4.3 Data Validation
2.4.4 Research Approach
2.5 Research Sources
2.5.1 Primary Research Sources
2.5.2 Secondary Research Sources
2.5.3 Assumptions
3 Market Trend Analysis
3.1 Introduction
3.2 Drivers
3.3 Restraints
3.4 Opportunities
3.5 Threats
3.6 Application Analysis
3.7 End User Analysis
3.8 Emerging Markets
3.9 Impact of Covid-19
4 Porters Five Force Analysis
4.1 Bargaining power of suppliers
4.2 Bargaining power of buyers
4.3 Threat of substitutes
4.4 Threat of new entrants
4.5 Competitive rivalry
5 Global Artificial Intelligence (AI) in Medical Imaging Market, By Imaging Modality
5.1 Introduction
5.2 X-Ray
5.3 Computed Tomography (CT)
5.4 Magnetic Resonance Imaging (MRI)
5.5 Ultrasound
5.6 Positron Emission Tomography (PET)
5.7 Mammography
5.8 Other Imaging Modalities
6 Global Artificial Intelligence (AI) in Medical Imaging Market, By AI Type
6.1 Introduction
6.2 Machine Learning
6.3 Deep Learning
6.4 Natural Language Processing (NLP)
6.5 Computer Vision
7 Global Artificial Intelligence (AI) in Medical Imaging Market, By Clinical Area
7.1 Introduction
7.2 Radiology
7.3 Cardiology
7.4 Neurology
7.5 Breast Screening/Breast Imaging
7.6 Oncology
7.7 Respiratory & Pulmonary
7.8 Orthopedics
7.9 Other Clinical Areas
8 Global Artificial Intelligence (AI) in Medical Imaging Market, By Deployment Model
8.1 Introduction
8.2 On-Premise
8.3 Cloud-based
8.4 Hybrid
9 Global Artificial Intelligence (AI) in Medical Imaging Market, By Component
9.1 Introduction
9.2 Software
9.2.1 AI Algorithms & Models
9.2.2 AI Platforms & Frameworks
9.2.3 AI-Powered Applications
9.3 Hardware
9.3.1 Specialized Processors
9.3.2 High-Performance Computing (HPC) Systems
9.3.3 Storage Solutions
9.3.4 AI-Integrated Imaging Devices
9.4 Services
9.4.1 Consulting Services
9.4.2 Implementation & Integration Services
9.4.3 Data Annotation & Curation Services
10 Global Artificial Intelligence (AI) in Medical Imaging Market, By Application
10.1 Introduction
10.2 Image analysis & Interpretation
10.3 Computer-Aided Diagnosis (CAD)
10.4 Quantitative Imaging & Biomarkers
10.5 Detection & Classification
10.6 Workflow Optimization & Triage
10.7 Other Applications
11 Global Artificial Intelligence (AI) in Medical Imaging Market, By End User
11.1 Introduction
11.2 Hospitals
11.3 Diagnostic Imaging Centers
11.4 Research Laboratories & Academic Institutions
11.5 Pharmaceutical & Biotechnology Companies
11.6 Other End Users
12 Global Artificial Intelligence (AI) in Medical Imaging Market, By Geography
12.1 Introduction
12.2 North America
12.2.1 US
12.2.2 Canada
12.2.3 Mexico
12.3 Europe
12.3.1 Germany
12.3.2 UK
12.3.3 Italy
12.3.4 France
12.3.5 Spain
12.3.6 Rest of Europe
12.4 Asia Pacific
12.4.1 Japan
12.4.2 China
12.4.3 India
12.4.4 Australia
12.4.5 New Zealand
12.4.6 South Korea
12.4.7 Rest of Asia Pacific
12.5 South America
12.5.1 Argentina
12.5.2 Brazil
12.5.3 Chile
12.5.4 Rest of South America
12.6 Middle East & Africa
12.6.1 Saudi Arabia
12.6.2 UAE
12.6.3 Qatar
12.6.4 South Africa
12.6.5 Rest of Middle East & Africa
13 Key Developments
13.1 Agreements, Partnerships, Collaborations and Joint Ventures
13.2 Acquisitions & Mergers
13.3 New Product Launch
13.4 Expansions
13.5 Other Key Strategies
12 Company Profiling
12.1 Aidoc
12.2 Arterys
12.3 Avicenna.AI
12.4 Canon Medical Systems Corporation
12.5 CureMetrix
12.6 Enlitic
12.7 GE HealthCare
12.8 HeartFlow Inc.
12.9 IBM Watson Health
12.10 Infervision
12.11 Lunit Inc.
12.12 Philips Healthcare
12.13 Qure.ai
12.14 RadNet
12.15 Riverain Technologies
12.16 ScreenPoint Medical
12.17 Siemens Healthineers
12.18 Therapixel
12.19 Zebra Medical Vision
List of Tables
1 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Region (2024-2032) ($MN)
2 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Imaging Modality (2024-2032) ($MN)
3 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By X-Ray (2024-2032) ($MN)
4 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Computed Tomography (CT) (2024-2032) ($MN)
5 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Magnetic Resonance Imaging (MRI) (2024-2032) ($MN)
6 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Ultrasound (2024-2032) ($MN)
7 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Positron Emission Tomography (PET) (2024-2032) ($MN)
8 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Mammography (2024-2032) ($MN)
9 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Other Imaging Modalities (2024-2032) ($MN)
10 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By AI Type (2024-2032) ($MN)
11 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Machine Learning (2024-2032) ($MN)
12 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Deep Learning (2024-2032) ($MN)
13 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Natural Language Processing (NLP) (2024-2032) ($MN)
14 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Computer Vision (2024-2032) ($MN)
15 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Clinical Area (2024-2032) ($MN)
16 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Radiology (2024-2032) ($MN)
17 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Cardiology (2024-2032) ($MN)
18 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Neurology (2024-2032) ($MN)
19 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Breast Screening/Breast Imaging (2024-2032) ($MN)
20 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Oncology (2024-2032) ($MN)
21 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Respiratory & Pulmonary (2024-2032) ($MN)
22 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Orthopedics (2024-2032) ($MN)
23 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Other Clinical Areas (2024-2032) ($MN)
24 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Deployment Model (2024-2032) ($MN)
25 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By On-Premise (2024-2032) ($MN)
26 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Cloud-based (2024-2032) ($MN)
27 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Hybrid (2024-2032) ($MN)
28 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Component (2024-2032) ($MN)
29 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Software (2024-2032) ($MN)
30 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By AI Algorithms & Models (2024-2032) ($MN)
31 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By AI Platforms & Frameworks (2024-2032) ($MN)
32 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By AI-Powered Applications (2024-2032) ($MN)
33 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Hardware (2024-2032) ($MN)
34 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Specialized Processors (2024-2032) ($MN)
35 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By High-Performance Computing (HPC) Systems (2024-2032) ($MN)
36 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Storage Solutions (2024-2032) ($MN)
37 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By AI-Integrated Imaging Devices (2024-2032) ($MN)
38 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Services (2024-2032) ($MN)
39 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Consulting Services (2024-2032) ($MN)
40 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Implementation & Integration Services (2024-2032) ($MN)
41 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Data Annotation & Curation Services (2024-2032) ($MN)
42 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Application (2024-2032) ($MN)
43 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Image analysis & Interpretation (2024-2032) ($MN)
44 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Computer-Aided Diagnosis (CAD) (2024-2032) ($MN)
45 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Quantitative Imaging & Biomarkers (2024-2032) ($MN)
46 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Detection & Classification (2024-2032) ($MN)
47 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Workflow Optimization & Triage (2024-2032) ($MN)
48 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Other Applications (2024-2032) ($MN)
49 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By End User (2024-2032) ($MN)
50 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Hospitals (2024-2032) ($MN)
51 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Diagnostic Imaging Centers (2024-2032) ($MN)
52 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Research Laboratories & Academic Institutions (2024-2032) ($MN)
53 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Pharmaceutical & Biotechnology Companies (2024-2032) ($MN)
54 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Other End Users (2024-2032) ($MN)
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
List of Figures
RESEARCH METHODOLOGY
We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
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