Radiology AI Market by Offering (On-Device, SaaS), Function (Triage, Workflow, CDSS, Acquisition, Processing, Reporting), Modality (CT, MRI, X-ray), Indication (Onco, Cardio, Neuro), End User (Hospital, Imaging Center), Region - Global Forecast to 2030
Description
The radiology AI market is projected to reach USD 2.27 billion by 2030 from USD 0.76 billion in 2025, at a CAGR of 24.5%. The growth is fueled by the increasing adoption of AI-driven diagnostic tools for early cancer detection, lesion segmentation, and predictive treatment planning, which enhance diagnostic accuracy and reduce radiologist workload. The expanding application of these solutions in oncology, neuroimaging, and cardiovascular imaging is significantly boosting demand for intelligent AI platforms capable of delivering real-time insights, personalized diagnostics, and workflow optimization, creating a high-value opportunity in the healthcare technology landscape.
The workflow optimization segment is expected to witness significant market share during the forecast period.
Based on the function, the radiology AI market is segmented into screening & triage, diagnostic imaging & interpretation (image acquisition, reconstruction & enhancement, image processing, analysis & detection, clinical decision support, others), treatment planning & intervention support (dose planning & optimization, surgical planning & guidance, image-based segmentation & anatomical modeling, others), monitoring & follow-up, reporting & documentation, workflow optimization, research & clinical development, and others. Workflow optimization is projected to record the fastest CAGR in the radiology AI market, driven by its strong economic and operational impact across imaging departments. With global radiologist shortages and rising imaging volumes, health systems are prioritizing AI that enhances productivity through intelligent worklist orchestration and automated case routing, as well as real-time modality utilization and turnaround-time reduction. These solutions streamline communication between technologists and radiologists, reduce the need for repeat scans, facilitate protocol standardization, and help eliminate manual administrative tasks. As hospitals increasingly shift toward value-based care, workflow AI directly supports cost containment, faster patient throughput, and an improved patient experience, making it a key investment area over the forecast period.
The software/SaaS segment is expected to have the largest share in 2025 in the radiology AI market.
By offering, the software/SaaS solutions segment is expected to hold the largest market share in 2025, primarily because they are easier to deploy, update, and scale across multiple imaging modalities. These platforms seamlessly integrate with existing Picture Archiving and Communication Systems (PACS), Radiology Information Systems (RIS), and Electronic Health Record (EHR) systems, enabling radiologists to access AI insights directly within their routine workflows without requiring major infrastructure changes. Cloud-based architectures enhance accessibility, support continuous model improvement, and lower upfront capital expenditure.
Additionally, software vendors leverage subscription and usage-based pricing, making adoption budget-friendly while driving strong recurring revenue. Growing regulatory approvals for diagnostic AI tools, along with strong use cases in oncology, neurology, and cardiology, further accelerate the dominance of this technology in the market.
The North America region accounted for a substantial share of the radiology AI market in 2025.
The North American region accounted for a substantial share of the radiology AI market in 2025, driven by significant investments in healthcare infrastructure, the adoption of advanced technology, and high demand for imaging services. The US, in particular, has seen widespread integration of AI into radiology workflows, supported by federal incentives for digital health adoption and regulatory approvals for AI-powered diagnostic tools. In addition, the growing prevalence of chronic diseases such as cancer, cardiovascular disorders, and neurological conditions has increased the demand for advanced imaging solutions, fueling the adoption of AI algorithms for image analysis, triage, and workflow optimization. For instance, in April 2025, according to the NIHCM Foundation, chronic diseases continue to pose a major burden on the US healthcare system, accounting for approximately 90% of the USD 4.5 trillion spent on healthcare in 2022, affecting around 60% of people in the US with multiple chronic conditions, thus driving high costs and complex care needs.
Robust investment from both private and public sectors, along with a high concentration of AI startups and established technology companies, further reinforced North American market leadership. Companies such as Aidoc (US), Enlitic, Inc. (US), and GE HealthCare (US) are actively developing AI-enabled platforms for CT, MRI, X-ray, and PET imaging, enhancing diagnostic accuracy and operational efficiency.
However, challenges such as data privacy concerns under HIPAA and clinician hesitancy to fully adopt AI tools remain. Despite these hurdles, the region continues to lead the global radiology AI market due to a combination of advanced healthcare infrastructure, favorable reimbursement policies, high R&D investment, and early adoption of innovative AI technologies.
These factors collectively reinforce North America’s leadership in the radiology AI market.
The breakdown of primary participants is as mentioned below:
The key players functioning in the radiology AI market include Siemens Healthineers AG (Germany), Microsoft (US), Koninklijke Philips N.V. (Netherlands), GE HealthCare (US), Fujifilm Holdings Corporation (Japan), Canon Medical Systems Corporation (Japan), Merative (US), DeepHealth (RadNet, Inc.) (US), Shanghai United Imaging Healthcare Co., LTD (China), Hologic, Inc. (US), and Enlitic, Inc. (US).
Research Coverage:
The report analyses the radiology AI market. It aims to estimate the market size and future growth potential of various market segments based on offering, function, modality, indication, end user, and region. The report also provides a competitive analysis of the key players in this market, along with their company profiles, product offerings, recent developments, and key market strategies.
Reasons to Buy the Report
This report will help established firms and new entrants/smaller firms gauge the market's pulse, which, in turn, will help them garner a greater share of the market. Firms purchasing the report could use one or a combination of the following strategies to strengthen their positions in the market.
This report provides insights into:
The workflow optimization segment is expected to witness significant market share during the forecast period.
Based on the function, the radiology AI market is segmented into screening & triage, diagnostic imaging & interpretation (image acquisition, reconstruction & enhancement, image processing, analysis & detection, clinical decision support, others), treatment planning & intervention support (dose planning & optimization, surgical planning & guidance, image-based segmentation & anatomical modeling, others), monitoring & follow-up, reporting & documentation, workflow optimization, research & clinical development, and others. Workflow optimization is projected to record the fastest CAGR in the radiology AI market, driven by its strong economic and operational impact across imaging departments. With global radiologist shortages and rising imaging volumes, health systems are prioritizing AI that enhances productivity through intelligent worklist orchestration and automated case routing, as well as real-time modality utilization and turnaround-time reduction. These solutions streamline communication between technologists and radiologists, reduce the need for repeat scans, facilitate protocol standardization, and help eliminate manual administrative tasks. As hospitals increasingly shift toward value-based care, workflow AI directly supports cost containment, faster patient throughput, and an improved patient experience, making it a key investment area over the forecast period.
The software/SaaS segment is expected to have the largest share in 2025 in the radiology AI market.
By offering, the software/SaaS solutions segment is expected to hold the largest market share in 2025, primarily because they are easier to deploy, update, and scale across multiple imaging modalities. These platforms seamlessly integrate with existing Picture Archiving and Communication Systems (PACS), Radiology Information Systems (RIS), and Electronic Health Record (EHR) systems, enabling radiologists to access AI insights directly within their routine workflows without requiring major infrastructure changes. Cloud-based architectures enhance accessibility, support continuous model improvement, and lower upfront capital expenditure.
Additionally, software vendors leverage subscription and usage-based pricing, making adoption budget-friendly while driving strong recurring revenue. Growing regulatory approvals for diagnostic AI tools, along with strong use cases in oncology, neurology, and cardiology, further accelerate the dominance of this technology in the market.
The North America region accounted for a substantial share of the radiology AI market in 2025.
The North American region accounted for a substantial share of the radiology AI market in 2025, driven by significant investments in healthcare infrastructure, the adoption of advanced technology, and high demand for imaging services. The US, in particular, has seen widespread integration of AI into radiology workflows, supported by federal incentives for digital health adoption and regulatory approvals for AI-powered diagnostic tools. In addition, the growing prevalence of chronic diseases such as cancer, cardiovascular disorders, and neurological conditions has increased the demand for advanced imaging solutions, fueling the adoption of AI algorithms for image analysis, triage, and workflow optimization. For instance, in April 2025, according to the NIHCM Foundation, chronic diseases continue to pose a major burden on the US healthcare system, accounting for approximately 90% of the USD 4.5 trillion spent on healthcare in 2022, affecting around 60% of people in the US with multiple chronic conditions, thus driving high costs and complex care needs.
Robust investment from both private and public sectors, along with a high concentration of AI startups and established technology companies, further reinforced North American market leadership. Companies such as Aidoc (US), Enlitic, Inc. (US), and GE HealthCare (US) are actively developing AI-enabled platforms for CT, MRI, X-ray, and PET imaging, enhancing diagnostic accuracy and operational efficiency.
However, challenges such as data privacy concerns under HIPAA and clinician hesitancy to fully adopt AI tools remain. Despite these hurdles, the region continues to lead the global radiology AI market due to a combination of advanced healthcare infrastructure, favorable reimbursement policies, high R&D investment, and early adoption of innovative AI technologies.
These factors collectively reinforce North America’s leadership in the radiology AI market.
The breakdown of primary participants is as mentioned below:
- By Company Type - Tier 1: 45%, Tier 2: 30%, and Tier 3: 25%
- By Designation – C Level: 40%, Director Level: 30%, and Others: 30%
- By Region - North America: 40%, Europe: 30%, Asia Pacific: 25%, Latin America: 3%, Middle East & Africa: 2%
The key players functioning in the radiology AI market include Siemens Healthineers AG (Germany), Microsoft (US), Koninklijke Philips N.V. (Netherlands), GE HealthCare (US), Fujifilm Holdings Corporation (Japan), Canon Medical Systems Corporation (Japan), Merative (US), DeepHealth (RadNet, Inc.) (US), Shanghai United Imaging Healthcare Co., LTD (China), Hologic, Inc. (US), and Enlitic, Inc. (US).
Research Coverage:
The report analyses the radiology AI market. It aims to estimate the market size and future growth potential of various market segments based on offering, function, modality, indication, end user, and region. The report also provides a competitive analysis of the key players in this market, along with their company profiles, product offerings, recent developments, and key market strategies.
Reasons to Buy the Report
This report will help established firms and new entrants/smaller firms gauge the market's pulse, which, in turn, will help them garner a greater share of the market. Firms purchasing the report could use one or a combination of the following strategies to strengthen their positions in the market.
This report provides insights into:
- Analysis of key drivers: Drivers (increasing medical imaging volumes, rising demand for AI solutions to alleviate radiologist workload, increase in regulatory clarity, accelerated approvals and government support, growing demand for AI-driven radiological image processing, growing funding for AI-focused startups, and rising collaborations with AI, tech, and analytics solution providers, Restraints (high implementation costs and ROI uncertainty, regulatory fragmentation across regions, and data quality and label scarcity for rarer indications), Opportunities (Growing demand for platform, multi-modal data, and OEM integration [PACS/EHR/marketplaces], untapped growth potential in emerging healthcare markets, expansion of preventive care and population health management, and expansion of portable or handheld devices with AI integration), Challenges (integration challenges with legacy radiology systems, limited clinician trust and explainability demands, and concerns over data privacy and security) influencing the growth of the radiology AI market.
- Product Development/Innovation: Detailed insights into upcoming technologies, research & development activities, and new product launches in the radiology AI market
- Market Development: Comprehensive information on the lucrative emerging markets, by offering, function, modality, indication, end user, and region.
- Market Diversification: Exhaustive information about the product portfolios, growing geographies, recent developments, and investments in the radiology AI market.
- Competitive Assessment: In-depth assessment of market shares, growth strategies, product offerings, and capabilities of the leading players in the radiology AI market such as Siemens Healthineers AG (Germany), Microsoft (US), Koninklijke Philips N.V. (Netherlands), GE HealthCare (US), Fujifilm Holdings Corporation (Japan), Canon Medical Systems Corporation (Japan), Merative (US), DeepHealth (RadNet, Inc.) (US), Shanghai United Imaging Healthcare Co., LTD (China), Hologic, Inc. (US), and Enlitic, Inc. (US).
Table of Contents
347 Pages
- 1 Introduction
- 1.1 Study Objectives
- 1.2 Market Definition
- 1.3 Study Scope
- 1.3.1 Market Segmentation & Regional Scope
- 1.3.2 Inclusions & Exclusions
- 1.3.3 Years Considered
- 1.4 Currency
- 1.5 Stakeholders
- 2 Executive Summary
- 2.1 Key Insights & Market Highlights
- 2.2 Key Market Participants: Share Insights & Strategic Developments
- 2.3 Disruptive Trends Shaping Market
- 2.4 High-growth Segments & Emerging Frontiers
- 2.5 Snapshot: Global Market Size, Growth Rate, And Forecast
- 3 Premium Insights
- 3.1 Radiology Ai Market Overview
- 3.2 North America: Radiology Ai Market, By Offering & Country
- 3.3 Radiology Ai Market: Geographic Snapshot
- 4 Market Overview
- 4.1 Introduction
- 4.2 Market Dynamics
- 4.2.1 Drivers
- 4.2.1.1 Increasing Medical Imaging Volumes
- 4.2.1.2 Rising Demand For Ai Solutions To Alleviate Radiologist Workload
- 4.2.1.3 Increased Regulatory Clarity, Accelerated Approvals, And Government Support
- 4.2.1.4 Growing Demand For Ai-driven Radiological Image Processing
- 4.2.1.5 Growing Funding For Ai-focused Startups
- 4.2.1.6 Rising Collaborations With Ai, Tech, And Analytics Solution Providers
- 4.2.2 Restraints
- 4.2.2.1 High Implementation Costs And Roi Uncertainty
- 4.2.2.2 Regulatory Fragmentation Across Regions
- 4.2.2.3 Data Quality And Label Scarcity For Rarer Indications
- 4.2.3 Opportunities
- 4.2.3.1 Growing Demand For Platform, Multi-modal Data, And Oem Integration (Pacs/Ehr/Marketplaces)
- 4.2.3.2 Untapped Growth Potential In Emerging Healthcare Markets
- 4.2.3.3 Expansion Of Preventive Care And Population Health Management
- 4.2.3.4 Expansion Of Portable/Handheld Devices With Ai Integration
- 4.2.4 Challenges
- 4.2.4.1 Integration Challenges With Legacy Radiology Systems
- 4.2.4.2 Limited Clinician Trust And Explainability Demands
- 4.2.4.3 Concerns Over Data Privacy And Security
- 4.3 Unmet Needs & White Spaces
- 4.4 Interconnected Markets & Cross-sector Opportunities
- 4.5 Strategic Moves By Tier-1/2/3 Players
- 5 Industry Trends
- 5.1 Porter’s Five Forces Analysis
- 5.1.1 Bargaining Power Of Suppliers
- 5.1.2 Bargaining Power Of Buyers
- 5.1.3 Threat Of Substitutes
- 5.1.4 Threat Of New Entrants
- 5.1.5 Intensity Of Competitive Rivalry
- 5.2 Macroeconomic Indicators
- 5.2.1 Introduction
- 5.2.2 Gdp Trends & Forecast
- 5.2.3 Trends In Global Healthcare It Industry
- 5.3 Supply Chain Analysis
- 5.4 Ecosystem Analysis
- 5.5 Pricing Analysis
- 5.5.1 Indicative Pricing For Radiology Ai Solutions, By Offering (2024)
- 5.5.2 Indicative Pricing For Radiology Ai Solutions, By Region (2024)
- 5.6 Key Conferences & Events, 2026–2027
- 5.7 Trends/Disruptions Impacting Customers’ Businesses
- 5.8 Investment & Funding Scenario
- 5.9 Case Study Analysis
- 5.10 Impact Of 2025 Us Tariffs On Radiology Ai Market
- 5.10.1 Introduction
- 5.10.2 Key Tariff Rates
- 5.10.3 Price Impact Analysis
- 5.10.4 Impact On Country/Region
- 5.10.4.1 Us
- 5.10.4.2 Europe
- 5.10.4.3 Asia Pacific
- 5.10.5 Impact On End-use Industries
- 5.10.5.1 Hospitals & Healthcare Systems
- 5.10.5.2 Diagnostic Imaging Centers & Independent Radiology Practices
- 5.10.5.3 Academic, Research, And Life Science Institutions
- 6 Technological Advancements, Ai-driven Impact, Patents, Innovations, And Future Applications
- 6.1 Key Emerging Technologies
- 6.1.1 Generative Ai For Image Reconstruction
- 6.1.2 Multimodal Ai Integration
- 6.1.3 Federated Learning Frameworks
- 6.2 Complementary Technologies
- 6.2.1 Cloud-based Imaging Platforms
- 6.2.2 Blockchain For Data Integrity & Traceability
- 6.2.3 Advanced Visualization & Ar/Vr Tools
- 6.3 Technology/Product Roadmap
- 6.4 Patent Analysis
- 6.4.1 Patent Publication Trends For Radiology Ai Market
- 6.4.2 Insights: Jurisdiction & Top Applicant Analysis
- 6.5 Future Applications
- 6.5.1 Ai-driven Precision Radiology & Personalized Treatment Planning
- 6.5.2 Autonomous Imaging & Workflow Orchestration
- 6.5.3 Predictive & Preventive Diagnostic Platforms
- 7 Regulatory Landscape
- 7.1 Regional Regulations & Compliance
- 7.1.1 Regulatory Bodies, Government Agencies, And Other Organizations
- 7.1.2 Regulatory Framework
- 7.1.2.1 North America
- 7.1.2.2 Europe
- 7.1.2.3 Asia Pacific
- 7.1.2.4 Latin America
- 7.1.2.5 Middle East & Africa
- 7.1.3 Industry Standards
- 8 Customer Landscape & Buyer Behavior
- 8.1 Decision-making Process
- 8.2 Buyer Stakeholders & Buying Evaluation Criteria
- 8.2.1 Key Stakeholders In Buying Process
- 8.2.2 Buying Criteria
- 8.3 Adoption Barriers & Internal Challenges
- 8.4 Unmet Needs From Various End-use Industries
- 8.4.1 Unmet Needs
- 8.4.2 End-user Expectations
- 8.5 Market Profitability
- 9 Radiology Ai Market, By Offering
- 9.1 Introduction
- 9.2 On-device Software
- 9.2.1 Rising Demand For Real-time, Secure, And Low-latency Diagnostic Intelligence To Accelerate Adoption
- 9.3 Software/Saas
- 9.3.1 Growing Demand For Scalable, Cost-efficient, Cloud-based Radiology Ai To Support Market Growth
- 10 Radiology Ai Market, By Function
- 10.1 Introduction
- 10.2 Screening & Triage
- 10.2.1 Rising Need For Rapid Identification And Prioritization Of Critical Findings To Drive Adoption Of Screening & Triage Ai
- 10.3 Diagnostic Imaging & Interpretation
- 10.3.1 Growing Demand For Higher Diagnostic Accuracy And Workload Reduction To Accelerate Adoption
- 10.4 Treatment Planning & Intervention Support
- 10.4.1 Rising Demand For Precise, Personalized Treatment Planning To Support Market Growth
- 10.5 Monitoring & Follow-up
- 10.5.1 Rising Need For Quantitative, Long-term Disease Monitoring To Boost Market Growth
- 10.6 Reporting & Documentation
- 10.6.1 Growing Need For Standardized, Automated Radiology Reporting To Contribute To Growth
- 10.7 Workflow Optimization
- 10.7.1 Rising Need For Efficient, Automated Radiology Workflows To Fuel Growth
- 10.8 Research & Clinical Development
- 10.8.1 Growing Demand For Ai-accelerated Imaging Research To Propel Market
- 10.9 Other Functions
- 11 Radiology Ai Market, By Modality
- 11.1 Introduction
- 11.2 Ct
- 11.2.1 Growing Need For Faster, More Accurate Ct Diagnosis To Drive Market Growth
- 11.3 Mri
- 11.3.1 Ongoing Technological Advancements In Mri Technology To Support Growth
- 11.4 X-ray
- 11.4.1 Growing Need To Manage Rising Imaging Volumes To Drive Demand For Ai-enhanced X-ray Systems
- 11.5 Ultrasound
- 11.5.1 Advantages Such As Minimally Invasive Nature, Low Cost, And Absence Of Ionizing Radiation To Boost Adoption
- 11.6 Mammography
- 11.6.1 Rising Breast Cancer Burden To Drive Ai Adoption In Mammography
- 11.7 Other Modalities
- 12 Radiology Ai Market, By Indication
- 12.1 Introduction
- 12.2 Oncology
- 12.2.1 Rising Global Cancer Burden To Accelerate Need For Ai-driven Diagnostics
- 12.3 Cardiology
- 12.3.1 Growing Cardiovascular Disease Prevalence To Boost Adoption Of Cardiac Imaging Ai
- 12.4 Neurology
- 12.4.1 Increasing Stroke And Neurodegenerative Cases To Drive Rapid Ai Integration
- 12.5 Pulmonology/Respiratory Diseases
- 12.5.1 Expanding Lung Disease Incidence To Fuel Demand For Ai-based Detection
- 12.6 Orthopedics
- 12.6.1 Rising Trauma And Osteoarthritis Cases To Increase Need For Msk Ai
- 12.7 Women’s Health
- 12.7.1 Growing Breast Cancer Screening Volumes To Accelerate Ai-enabled Imaging Adoption
- 12.8 Other Indications
- 13 Radiology Ai Market, By End User
- 13.1 Introduction
- 13.2 Hospitals
- 13.2.1 Increasing Deployment Of Advanced Radiology Ai-enabled Imaging Systems In Hospitals To Drive Market Growth
- 13.3 Diagnostic Imaging Centers
- 13.3.1 Rising Volume Of Imaging Procedures To Strengthen Need For Ai-supported Image Interpretation
- 13.4 Other End Users
- 14 Radiology Ai Market, By Region
- 14.1 Introduction
- 14.2 North America
- 14.2.1 Macroeconomic Outlook For North America
- 14.2.2 Us
- 14.2.2.1 Us To Dominate Global Radiology Ai Market
- 14.2.3 Canada
- 14.2.3.1 Growing Integration Of Ai In Radiology Supported By Strong Research & Regulatory Frameworks To Drive Market
- 14.3 Europe
- 14.3.1 Macroeconomic Outlook For Europe
- 14.3.2 Germany
- 14.3.2.1 Growing Need To Advance Diagnostic Precision Through Ai-driven Imaging To Boost Market
- 14.3.3 France
- 14.3.3.1 Need To Address Regulatory, Ethical, And Integration Challenges In France’s Radiology Ai Market To Boost Growth
- 14.3.4 Uk
- 14.3.4.1 Accelerating Ai Integration In Diagnostic Imaging Across Nhs To Spur Market Growth
- 14.3.5 Italy
- 14.3.5.1 Regulatory Complexity And Infrastructure Gaps To Constrain Radiology Ai Expansion
- 14.3.6 Spain
- 14.3.6.1 Advancing Digital Imaging And Ai Integration Across Spain’s Healthcare System To Support Growth
- 14.3.7 Rest Of Europe
- 14.4 Asia Pacific
- 14.4.1 Macroeconomic Outlook For Asia Pacific
- 14.4.2 Japan
- 14.4.2.1 Strong Digital Health Infrastructure And Government-led Innovation Programs To Support Growth
- 14.4.3 China
- 14.4.3.1 Rapid Adoption And Scale-up Of Ai-enabled Radiology In China To Drive Growth
- 14.4.4 India
- 14.4.4.1 Rising Imaging Volumes And Need For Scalable Diagnostic Solutions To Fuel Growth
- 14.4.5 South Korea
- 14.4.5.1 Integration And Validation Challenges In South Korea’s Radiology Ai Market To Slow Growth
- 14.4.6 Australia
- 14.4.6.1 Scaling Clinical Ai From Pilot Programs To Nationwide Deployment To Boost Market
- 14.4.7 Rest Of Asia Pacific
- 14.5 Latin America
- 14.5.1 Macroeconomic Outlook For Latin America
- 14.5.2 Brazil
- 14.5.2.1 Expanding Clinical Integration And Local Innovation In Radiology Ai To Fuel Market
- 14.5.3 Mexico
- 14.5.3.1 Integration And Regulatory Barriers To Hinder Ai Adoption In Radiology
- 14.5.4 Rest Of Latin America
- 14.6 Middle East & Africa
- 14.6.1 Macroeconomic Outlook For Middle East & Africa
- 14.6.2 Gcc Countries
- 14.6.2.1 Saudi Arabia
- 14.6.2.1.1 Advancing Diagnostic Intelligence Through Healthcare Digitalization And Ai Integration To Fuel Growth
- 14.6.2.2 Uae
- 14.6.2.2.1 Accelerating Smart Healthcare Transformation Through Ai-enabled Radiology To Spur Growth
- 14.6.2.3 Rest Of Gcc Countries
- 14.6.3 South Africa
- 14.6.3.1 Growing Integration Of Ai To Strengthen Diagnostic Imaging And Clinical Efficiency
- 14.6.4 Rest Of Middle East & Africa
- 15 Competitive Landscape
- 15.1 Overview
- 15.2 Key Player Strategies/Right To Win
- 15.2.1 Overview Of Strategies Adopted By Key Players In Radiology Ai Market
- 15.3 Revenue Analysis, 2020–2024
- 15.4 Market Share Analysis, 2024
- 15.5 Brand/Software Comparison
- 15.6 Company Evaluation Matrix: Key Players, 2024
- 15.6.1 Stars
- 15.6.2 Emerging Leaders
- 15.6.3 Pervasive Players
- 15.6.4 Participants
- 15.6.5 Company Footprint: Key Players, 2024
- 15.6.5.1 Company Footprint
- 15.6.5.2 Region Footprint
- 15.6.5.3 Offering Footprint
- 15.6.5.4 Function Footprint
- 15.6.5.5 Modality Footprint
- 15.6.5.6 End-user Footprint
- 15.7 Company Evaluation Matrix: Startups/Smes, 2024
- 15.7.1 Progressive Companies
- 15.7.2 Responsive Companies
- 15.7.3 Dynamic Companies
- 15.7.4 Starting Blocks
- 15.7.5 Competitive Benchmarking: Startups/Smes, 2024
- 15.7.5.1 Detailed List Of Key Startups/Smes
- 15.7.5.2 Competitive Benchmarking Of Startups/Smes
- 15.8 Company Valuation & Financial Metrics
- 15.8.1 Financial Metrics
- 15.8.2 Company Valuation
- 15.9 Competitive Scenario
- 15.9.1 Product Launches, Approvals, And Enhancements
- 15.9.2 Deals
- 15.9.3 Other Developments
- 15.10 Key Players
- 15.10.1 Siemens Healthineers Ag
- 15.10.1.1 Business Overview
- 15.10.1.2 Solutions Offered
- 15.10.1.3 Recent Developments
- 15.10.1.3.1 Product Launches
- 15.10.1.3.2 Deals
- 15.10.1.3.3 Other Developments
- 15.10.1.4 Mnm View
- 15.10.1.4.1 Right To Win
- 15.10.1.4.2 Strategic Choices
- 15.10.1.4.3 Weaknesses & Competitive Threats
- 15.10.2 Microsoft
- 15.10.2.1 Business Overview
- 15.10.2.2 Solutions Offered
- 15.10.2.3 Recent Developments
- 15.10.2.3.1 Product Launches
- 15.10.2.3.2 Deals
- 15.10.2.3.3 Other Developments
- 15.10.2.4 Mnm View
- 15.10.2.4.1 Right To Win
- 15.10.2.4.2 Strategic Choices
- 15.10.2.4.3 Weaknesses & Competitive Threats
- 15.10.3 Koninklijke Philips N.V.
- 15.10.3.1 Business Overview
- 15.10.3.2 Solutions Offered
- 15.10.3.3 Recent Developments
- 15.10.3.3.1 Product Launches & Approvals
- 15.10.3.3.2 Deals
- 15.10.3.3.3 Other Developments
- 15.10.3.4 Mnm View
- 15.10.3.4.1 Right To Win
- 15.10.3.4.2 Strategic Choices
- 15.10.3.4.3 Weaknesses & Competitive Threats
- 15.10.4 Ge Healthcare
- 15.10.4.1 Business Overview
- 15.10.4.2 Solutions Offered
- 15.10.4.3 Recent Developments
- 15.10.4.3.1 Product Launches & Approvals
- 15.10.4.3.2 Deals
- 15.10.4.3.3 Expansions
- 15.10.4.3.4 Other Developments
- 15.10.4.4 Mnm View
- 15.10.4.4.1 Right To Win
- 15.10.4.4.2 Strategic Choices
- 15.10.4.4.3 Weaknesses & Competitive Threats
- 15.10.5 Fujifilm Holdings Corporation
- 15.10.5.1 Business Overview
- 15.10.5.2 Solutions Offered
- 15.10.5.3 Recent Developments
- 15.10.5.3.1 Product Launches & Approvals
- 15.10.5.3.2 Deals
- 15.10.5.3.3 Other Developments
- 15.10.5.4 Mnm View
- 15.10.5.4.1 Right To Win
- 15.10.5.4.2 Strategic Choices
- 15.10.5.4.3 Weaknesses & Competitive Threats
- 15.10.6 Canon Medical Systems Corporation (Canon Inc.)
- 15.10.6.1 Business Overview
- 15.10.6.2 Solutions Offered
- 15.10.6.3 Recent Developments
- 15.10.6.3.1 Product Launches & Approvals
- 15.10.6.3.2 Deals
- 15.10.6.3.3 Other Developments
- 15.10.7 Merative
- 15.10.7.1 Business Overview
- 15.10.7.2 Solutions Offered
- 15.10.7.3 Recent Developments
- 15.10.7.3.1 Deals
- 15.10.7.3.2 Expansions
- 15.10.7.3.3 Other Developments
- 15.10.8 Radnet, Inc. (Deephealth)
- 15.10.8.1 Business Overview
- 15.10.8.2 Solutions Offered
- 15.10.8.3 Recent Developments
- 15.10.8.3.1 Product Launches & Approvals
- 15.10.8.3.2 Deals
- 15.10.9 Shanghai United Imaging Healthcare Co., Ltd.
- 15.10.9.1 Business Overview
- 15.10.9.2 Solutions Offered
- 15.10.9.3 Recent Developments
- 15.10.9.3.1 Product Launches & Approvals
- 15.10.9.3.2 Deals
- 15.10.9.3.3 Other Developments
- 15.10.10 Hologic, Inc.
- 15.10.10.1 Business Overview
- 15.10.10.2 Solutions Offered
- 15.10.10.3 Recent Developments
- 15.10.10.3.1 Product Launches & Approvals
- 15.10.10.3.2 Deals
- 15.10.10.3.3 Other Developments
- 15.10.11 Enlitic, Inc.
- 15.10.11.1 Business Overview
- 15.10.11.2 Solutions Offered
- 15.10.11.3 Recent Developments
- 15.10.11.3.1 Product Launches & Approvals
- 15.10.11.3.2 Deals
- 15.10.11.3.3 Other Developments
- 15.11 Other Players
- 15.11.1 Aidoc
- 15.11.2 Viz.Ai, Inc.
- 15.11.3 Nanox
- 15.11.4 Qure.Ai
- 15.11.5 Esaote S.P.A.
- 15.11.6 Butterfly Network Inc.
- 15.11.7 Heartflow Inc.
- 15.11.8 Subtle Medical, Inc.
- 15.11.9 Harisson.Ai
- 15.11.10 Echonous Inc.
- 15.11.11 Quibim
- 15.11.12 Imagen
- 15.11.13 Exo Imaging, Inc.
- 15.11.14 Rad Ai
- 16 Research Methodology
- 16.1 Research Data
- 16.1.1 Secondary Data
- 16.1.1.1 Key Data From Secondary Sources
- 16.1.2 Primary Data
- 16.1.2.1 Key Data From Primary Sources
- 16.1.2.2 Breakdown Of Primary Sources
- 16.2 Research Approach
- 16.3 Market Size Estimation
- 16.4 Market Breakdown & Data Triangulation
- 16.5 Research Assumptions
- 16.5.1 Market Sizing Assumptions
- 16.5.2 Overall Study Assumptions
- 16.6 Risk Assessment
- 16.7 Research Limitations
- 16.7.1 Methodology-related Limitations
- 16.7.2 Scope-related Limitations
- 17 Appendix
- 17.1 Discussion Guide
- 17.2 Knowledgestore: Marketsandmarkets’ Subscription Portal
- 17.3 Customization Options
- 17.4 Related Reports
- 17.5 Author Details
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