Ai In Diagnostic Imaging Market
AI in Diagnostic Imaging Market Forecasts to 2032 – Global Analysis By Component (Software, Hardware and Services), Modality (X-ray, MRI (Magnetic Resonance Imaging), CT (Computed Tomography), Ultrasound, PET (Positron Emission Tomography), Mammography and Other Modalities), Deployment Mode, Technology, Application, End User and By Geography
According to Stratistics MRC, the Global AI in Diagnostic Imaging Market is accounted for $1.6 billion in 2025 and is expected to reach $13.6 billion by 2032 growing at a CAGR of 35.4% during the forecast period. Artificial Intelligence in diagnostic imaging is the use of advanced algorithms and machine learning models to analyze medical images for improved accuracy, efficiency, and clinical decision-making. AI systems assist in detecting abnormalities, segmenting anatomical structures, and enhancing image quality across modalities such as MRI, CT, and X-ray. By automating routine tasks and identifying subtle patterns, AI supports radiologists in early disease detection, treatment planning, and workflow optimization, ultimately contributing to faster diagnoses and more personalized patient care
According to European Radiology identified 269 AI applications in diagnostic radiology, developed by 99 companies. These applications predominantly focus on narrow tasks such as perception and reasoning within specific imaging modalities and anatomical regions.
Market Dynamics:
Driver:
Rising demand for accurate and scalable diagnostics
AI algorithms are now capable of analyzing vast datasets from modalities like MRI, CT, and X-ray with remarkable precision, reducing diagnostic errors and accelerating clinical decision-making. Hospitals and imaging centers are adopting AI tools to streamline workflows, improve throughput, and enhance diagnostic accuracy, especially in high-volume settings. This shift is further supported by regulatory approvals and reimbursement frameworks that validate AI as a clinical asset.
Restraint:
High cost of implementation and integration
Despite its transformative potential, the integration of AI into diagnostic imaging systems remains financially challenging for many healthcare providers. The upfront investment in AI-enabled hardware, software licenses, and infrastructure upgrades such as cloud storage and cybersecurity can be prohibitive, particularly for mid-sized and rural facilities. Moreover, training personnel to operate and interpret AI outputs adds to operational costs. These financial barriers slow down the adoption, especially in regions with limited healthcare budgets or fragmented IT ecosystems.
Opportunity:
Integration with clinical workflows and multimodal AI
AI is increasingly being embedded into end-to-end diagnostic workflows, enabling seamless data exchange between imaging systems, electronic health records (EHRs), and clinical decision support tools. The rise of multimodal AI combining imaging data with genomics, pathology, and patient history is unlocking new possibilities for personalized diagnostics. Vendors are developing interoperable platforms that support real-time triage, predictive analytics, and longitudinal patient monitoring. This convergence is expected to redefine diagnostic precision and open new revenue streams for AI developers and healthcare providers.
Threat:
Algorithmic bias and lack of explainability
Bias in image interpretation can lead to misdiagnosis or delayed treatment, raising ethical and legal concerns. Additionally, many AI systems operate as “black boxes,” offering limited transparency into how conclusions are reached. This lack of explainability undermines clinician trust and complicates regulatory approval. Addressing these issues requires robust validation protocols, inclusive training datasets, and the development of interpretable AI frameworks.
Covid-19 Impact:
The COVID-19 pandemic accelerated the adoption of AI in diagnostic imaging, particularly for chest CT and X-ray analysis. AI tools were rapidly deployed to detect COVID-related anomalies, triage patients, and monitor disease progression. However, supply chain disruptions and resource reallocation toward pandemic response temporarily slowed non-COVID imaging volumes. Post-pandemic, the emphasis on preparedness and digital transformation is expected to sustain AI adoption, with increased investment in scalable, cloud-based imaging platforms.
The software segment is expected to be the largest during the forecast period
The software segment is expected to account for the largest market share during the forecast period due to its central role in enabling intelligent image analysis. AI software platforms integrate deep learning models, natural language processing, and predictive analytics to deliver actionable insights from complex imaging data. These platforms are increasingly cloud-based, allowing for scalable deployment across multiple facilities. Continuous updates and algorithm enhancements ensure adaptability to evolving clinical needs, making software the backbone of AI-driven diagnostics.
The MRI (magnetic resonance imaging) segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the MRI (magnetic resonance imaging) segment is predicted to witness the highest growth rate driven by its superior soft tissue contrast and expanding applications in neurology, oncology, and cardiology. AI integration enhances MRI by automating image segmentation, improving resolution, and reducing scan times. Innovations such as ultra-high-field MRI and AI-assisted functional imaging are enabling earlier detection of complex conditions like Alzheimer’s and multiple sclerosis. As demand for precision diagnostics grows, AI-powered MRI systems are becoming indispensable in advanced care settings.
Region with largest share:
During the forecast period, the North America region is expected to hold the largest market share supported by a robust healthcare infrastructure, high imaging volumes, and proactive regulatory frameworks. The region benefits from strong R&D investments, widespread adoption of digital health technologies, and favorable reimbursement policies for AI-enabled diagnostics. Major players like GE HealthCare, IBM Watson Health, and Siemens Healthineers are headquartered here, driving innovation and commercialization. The U.S. also leads in clinical trials and FDA approvals for AI-based imaging tools.
Region with highest CAGR:
Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR fueled by rising healthcare expenditure, expanding access to diagnostic services, and government initiatives promoting AI adoption. Countries like China, India, and Japan are investing heavily in digital health infrastructure and AI research. The region’s large patient population and increasing prevalence of chronic diseases create a fertile ground for AI-driven imaging solutions. Local startups and global players are forming strategic partnerships to tap into this rapidly evolving market.
Key players in the market
Some of the key players in AI in Diagnostic Imaging Market include Arterys, Aidoc, Zebra Medical Vision, Enlitic, Qure.ai, Infervision, Caption Health, Lunit, Butterfly Network, Gauss Surgical, Sigtuple, Freenome, Bay Labs, IBM Watson Health Imaging, Siemens Healthineers, GE Healthcare, and Philips Healthcare
Key Developments:
In July 2025, AZmed obtained two new FDA clearances for its AI-driven chest X-ray analytics technology, expanding its offerings in diagnostic imaging. These clearances facilitate broader clinical use, enhancing early detection and workflow automation in radiology practices.
In April 2025, Siemens Healthineers showcased its latest diagnostic imaging breakthroughs focused on improving healthcare through advanced AI-powered solutions. The company emphasized enhancing diagnostic productivity, accuracy, and patient outcomes with their cutting-edge imaging technologies during the Asia Oceania Congress of Radiology.
In March 2025, Gleamer acquired Pixyl and Caerus Medical, boosting their proprietary AI imaging portfolio with advanced FDA- and CE-cleared neuro and lumbar MRI AI applications. This expansion positions Gleamer as a leader with comprehensive AI solutions spanning X-ray, mammography, CT, and MRI modalities.
Components Covered:
• Software
• Hardware
• Services
Modalities Covered:
• X-ray
• MRI (Magnetic Resonance Imaging)
• CT (Computed Tomography)
• Ultrasound
• PET (Positron Emission Tomography)
• Mammography
• Other Modalities
Deployment Modes Covered:
• Cloud-Based
• On-Premises
Technologies Covered:
• Deep Learning
• Natural Language Processing (NLP)
• Computer Vision
• Generative Adversarial Networks (GANs)
• Other Technologies
Applications Covered:
• Oncology
• Cardiology
• Neurology
• Orthopedics
• Pulmonology
• Breast Imaging
• Liver & GI Imaging
• Oral Diagnostics
• Other Applications
End Users Covered:
• Hospitals
• Diagnostic Centers
• Research Laboratories
• Specialty Clinics
• 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 alliances
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 Technology Analysis
3.7 Application Analysis
3.8 End User Analysis
3.9 Emerging Markets
3.10 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 AI in Diagnostic Imaging Market, By Component
5.1 Introduction
5.2 Software
5.2.1 AI-based Platforms
5.2.2 Algorithms & Solutions
5.3 Hardware
5.3.1 Integrated AI-enabled Imaging Devices
5.3.2 Servers & Storage
5.3.3 GPUs & Processors
5.4 Services
5.4.1 Installation & Integration Services
5.4.2 Support & Maintenance
5.4.3 Training & Consulting
6 Global AI in Diagnostic Imaging Market, By Modality
6.1 Introduction
6.2 X-ray
6.3 MRI (Magnetic Resonance Imaging)
6.4 CT (Computed Tomography)
6.5 Ultrasound
6.6 PET (Positron Emission Tomography)
6.7 Mammography
6.8 Other Modalities
7 Global AI in Diagnostic Imaging Market, By Deployment Mode
7.1 Introduction
7.2 Cloud-Based
7.3 On-Premises
8 Global AI in Diagnostic Imaging Market, By Technology
8.1 Introduction
8.2 Deep Learning
8.3 Natural Language Processing (NLP)
8.4 Computer Vision
8.5 Generative Adversarial Networks (GANs)
8.6 Other Technologies
9 Global AI in Diagnostic Imaging Market, By Application
9.1 Introduction
9.2 Oncology
9.3 Cardiology
9.4 Neurology
9.5 Orthopedics
9.6 Pulmonology
9.7 Breast Imaging
9.8 Liver & GI Imaging
9.9 Oral Diagnostics
9.10 Other Applications
10 Global AI in Diagnostic Imaging Market, By End User
10.1 Introduction
10.2 Hospitals
10.3 Diagnostic Centers
10.4 Research Laboratories
10.5 Specialty Clinics
10.6 Other End Users
11 Global AI in Diagnostic Imaging Market, By Geography
11.1 Introduction
11.2 North America
11.2.1 US
11.2.2 Canada
11.2.3 Mexico
11.3 Europe
11.3.1 Germany
11.3.2 UK
11.3.3 Italy
11.3.4 France
11.3.5 Spain
11.3.6 Rest of Europe
11.4 Asia Pacific
11.4.1 Japan
11.4.2 China
11.4.3 India
11.4.4 Australia
11.4.5 New Zealand
11.4.6 South Korea
11.4.7 Rest of Asia Pacific
11.5 South America
11.5.1 Argentina
11.5.2 Brazil
11.5.3 Chile
11.5.4 Rest of South America
11.6 Middle East & Africa
11.6.1 Saudi Arabia
11.6.2 UAE
11.6.3 Qatar
11.6.4 South Africa
11.6.5 Rest of Middle East & Africa
12 Key Developments
12.1 Agreements, Partnerships, Collaborations and Joint Ventures
12.2 Acquisitions & Mergers
12.3 New Product Launch
12.4 Expansions
12.5 Other Key Strategies
13 Company Profiling
13.1 Arterys
13.2 Aidoc
13.3 Zebra Medical Vision
13.4 Enlitic
13.5 Qure.ai
13.6 Infervision
13.7 Caption Health
13.8 Lunit
13.9 Butterfly Network
13.10 Gauss Surgical
13.11 Sigtuple
13.12 Freenome
13.13 Bay Labs
13.14 IBM Watson Health Imaging
13.15 Siemens Healthineers
13.16 GE Healthcare
13.17 Philips Healthcare
List of Tables
1 Global AI in Diagnostic Imaging Market Outlook, By Region (2024-2032) ($MN)
2 Global AI in Diagnostic Imaging Market Outlook, By Component (2024-2032) ($MN)
3 Global AI in Diagnostic Imaging Market Outlook, By Software (2024-2032) ($MN)
4 Global AI in Diagnostic Imaging Market Outlook, By AI-based Platforms (2024-2032) ($MN)
5 Global AI in Diagnostic Imaging Market Outlook, By Algorithms & Solutions (2024-2032) ($MN)
6 Global AI in Diagnostic Imaging Market Outlook, By Hardware (2024-2032) ($MN)
7 Global AI in Diagnostic Imaging Market Outlook, By Integrated AI-enabled Imaging Devices (2024-2032) ($MN)
8 Global AI in Diagnostic Imaging Market Outlook, By Servers & Storage (2024-2032) ($MN)
9 Global AI in Diagnostic Imaging Market Outlook, By GPUs & Processors (2024-2032) ($MN)
10 Global AI in Diagnostic Imaging Market Outlook, By Services (2024-2032) ($MN)
11 Global AI in Diagnostic Imaging Market Outlook, By Installation & Integration Services (2024-2032) ($MN)
12 Global AI in Diagnostic Imaging Market Outlook, By Support & Maintenance (2024-2032) ($MN)
13 Global AI in Diagnostic Imaging Market Outlook, By Training & Consulting (2024-2032) ($MN)
14 Global AI in Diagnostic Imaging Market Outlook, By Modality (2024-2032) ($MN)
15 Global AI in Diagnostic Imaging Market Outlook, By X-ray (2024-2032) ($MN)
16 Global AI in Diagnostic Imaging Market Outlook, By MRI (Magnetic Resonance Imaging) (2024-2032) ($MN)
17 Global AI in Diagnostic Imaging Market Outlook, By CT (Computed Tomography) (2024-2032) ($MN)
18 Global AI in Diagnostic Imaging Market Outlook, By Ultrasound (2024-2032) ($MN)
19 Global AI in Diagnostic Imaging Market Outlook, By PET (Positron Emission Tomography) (2024-2032) ($MN)
20 Global AI in Diagnostic Imaging Market Outlook, By Mammography (2024-2032) ($MN)
21 Global AI in Diagnostic Imaging Market Outlook, By Other Modalities (2024-2032) ($MN)
22 Global AI in Diagnostic Imaging Market Outlook, By Deployment Mode (2024-2032) ($MN)
23 Global AI in Diagnostic Imaging Market Outlook, By Cloud-Based (2024-2032) ($MN)
24 Global AI in Diagnostic Imaging Market Outlook, By On-Premises (2024-2032) ($MN)
25 Global AI in Diagnostic Imaging Market Outlook, By Technology (2024-2032) ($MN)
26 Global AI in Diagnostic Imaging Market Outlook, By Deep Learning (2024-2032) ($MN)
27 Global AI in Diagnostic Imaging Market Outlook, By Natural Language Processing (NLP) (2024-2032) ($MN)
28 Global AI in Diagnostic Imaging Market Outlook, By Computer Vision (2024-2032) ($MN)
29 Global AI in Diagnostic Imaging Market Outlook, By Generative Adversarial Networks (GANs) (2024-2032) ($MN)
30 Global AI in Diagnostic Imaging Market Outlook, By Other Technologies (2024-2032) ($MN)
31 Global AI in Diagnostic Imaging Market Outlook, By Application (2024-2032) ($MN)
32 Global AI in Diagnostic Imaging Market Outlook, By Oncology (2024-2032) ($MN)
33 Global AI in Diagnostic Imaging Market Outlook, By Cardiology (2024-2032) ($MN)
34 Global AI in Diagnostic Imaging Market Outlook, By Neurology (2024-2032) ($MN)
35 Global AI in Diagnostic Imaging Market Outlook, By Orthopedics (2024-2032) ($MN)
36 Global AI in Diagnostic Imaging Market Outlook, By Pulmonology (2024-2032) ($MN)
37 Global AI in Diagnostic Imaging Market Outlook, By Breast Imaging (2024-2032) ($MN)
38 Global AI in Diagnostic Imaging Market Outlook, By Liver & GI Imaging (2024-2032) ($MN)
39 Global AI in Diagnostic Imaging Market Outlook, By Oral Diagnostics (2024-2032) ($MN)
40 Global AI in Diagnostic Imaging Market Outlook, By Other Applications (2024-2032) ($MN)
41 Global AI in Diagnostic Imaging Market Outlook, By End User (2024-2032) ($MN)
42 Global AI in Diagnostic Imaging Market Outlook, By Hospitals (2024-2032) ($MN)
43 Global AI in Diagnostic Imaging Market Outlook, By Diagnostic Centers (2024-2032) ($MN)
44 Global AI in Diagnostic Imaging Market Outlook, By Research Laboratories (2024-2032) ($MN)
45 Global AI in Diagnostic Imaging Market Outlook, By Specialty Clinics (2024-2032) ($MN)
46 Global AI in Diagnostic 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.
For more details about research methodology, kindly write to us at info@strategymrc.com
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