AI-Enabled Medical Imaging Solutions Market: Global And Regional Analysis And Forecast, 2026-2036 Market To Reach $18.04 Billion As Generative AI And Workflow Automation Scale

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Dublin, Oct. 16, 2026 (GLOBE NEWSWIRE) -- "AI-Enabled Medical Imaging Solutions Market - A Global and Regional Analysis: Focus on Modality, Product, Deployment Model, Workflow, Application, and Regional Analysis, 2026-2036" has been added to ResearchAndMarkets.com's offering.

The global AI-enabled medical imaging solutions market was valued at $2.58 billion in 2024 and is projected to reach $18.04 billion by 2036, registering a compound annual growth rate (CAGR) of 17.60% from 2026 to 2036. According to the report, market expansion is being driven by rising imaging volumes, radiologist shortages, growing demand for earlier disease detection, and the need for faster, more accurate diagnostic workflows.

Healthcare providers are increasingly integrating artificial intelligence across X-ray, Magnetic Resonance Imaging, Computed Tomography, ultrasound, and other imaging modalities. Key applications include image acquisition, reconstruction, analysis, abnormality detection, triage, reporting, predictive analytics, and clinical decision support. Adoption is accelerating across oncology, cardiology, neurology, pulmonology, breast imaging, trauma assessment, and musculoskeletal diagnostics.

Advances in deep learning-based image reconstruction, automated segmentation, computer-aided detection, predictive analytics, and generative AI-assisted reporting are improving diagnostic consistency and radiologist productivity. These technologies can also support shorter scan times, optimized image quality, lower radiation exposure, and faster reporting turnaround times. Integration with enterprise imaging platforms, PACS/RIS systems, and cloud-based infrastructure is further supporting scalable implementation across hospitals, diagnostic imaging centers, academic medical centers, and ambulatory care settings.

Market Segmentation Highlights

• By Product: The software segment is expected to account for the largest market share. Demand is supported by the ability to deploy AI-based image analysis, workflow automation, triage, reporting, reconstruction, and clinical decision support tools across existing imaging infrastructure.
• By Modality: Computed Tomography is projected to lead the market due to its extensive use in oncology, cardiology, neurology, pulmonology, trauma, and emergency care. AI-enabled CT applications support lesion detection, organ segmentation, dose reduction, quantitative analysis, image reconstruction, and workflow prioritization.
• By Deployment Model: On-premises solutions are expected to retain the largest share as major hospitals prioritize data security, cybersecurity management, regulatory control, and direct integration with existing PACS, RIS, enterprise imaging, and hospital IT systems.
• By Workflow: Image analysis is forecast to dominate, supported by broad demand for image enhancement, anatomical recognition, segmentation, quantification, abnormality characterization, and reconstruction across multiple specialties.
• By Therapeutic Application: Specialty imaging is expected to hold the leading position because of strong demand for AI-enabled CT, MRI, and advanced imaging capabilities in complex oncology, cardiology, neurology, and specialty care pathways.
• By Region: North America is projected to lead the global AI-enabled medical imaging solutions market, supported by advanced healthcare infrastructure, high digital imaging adoption, substantial purchasing capacity, rapid regulatory progress, and a large installed base of CT, MRI, X-ray, and ultrasound systems.

Growth Drivers and Market Opportunities

Growing emphasis on early detection and risk-based screening is a major market driver. Healthcare systems are expanding cancer screening, chronic disease assessment, and opportunistic detection programs to improve clinical outcomes and reduce downstream treatment burdens. AI-enabled imaging tools support automated detection, case prioritization, risk stratification, and diagnostic decision support, helping providers manage population-level screening initiatives more efficiently.

Healthcare workforce shortages also create significant commercial opportunities. Rising chronic disease prevalence, aging populations, broader screening programs, and higher demand for imaging services are increasing pressure on radiologists, radiographers, and imaging technologists. AI-based workflow augmentation can reduce repetitive tasks, prioritize urgent cases, assist with reporting, and improve consistency across high-volume imaging environments. This positions AI-enabled medical imaging solutions as an important investment area for healthcare organizations seeking greater operational efficiency without compromising clinical quality.

Market growth is reinforced by partnerships among imaging vendors, AI software developers, healthcare institutions, cloud platform providers, and research organizations. These collaborations are accelerating algorithm validation, product commercialization, workflow integration, and geographic expansion. Established imaging companies and specialized AI vendors are also broadening their modality-specific and disease-specific portfolios to address targeted clinical needs.

Market Challenges

Regulatory complexity, interoperability limitations, data privacy requirements, algorithm validation, and clinical integration remain key barriers. Legal and liability-related concerns are particularly important when AI-assisted findings contribute to false positives, missed abnormalities, delayed diagnoses, or unsuitable treatment decisions. Questions surrounding accountability among clinicians, healthcare institutions, and software vendors continue to influence procurement and deployment strategies.

Algorithmic bias, model transparency, informed consent, cybersecurity, and the black-box characteristics of some deep learning systems can also affect clinical trust. Consequently, many healthcare organizations continue to implement AI primarily as an assistive capability rather than an autonomous decision-making system. Clear governance frameworks, robust clinical evidence, and effective integration with established radiology workflows will remain essential for wider adoption.

Recent Industry Developments

• In March 2026, NVIDIA Corporation partnered with global robotics leaders to advance AI-enabled physical intelligence platforms, including imaging, perception, and decision-making applications relevant to healthcare automation and precision diagnostics.
• In January 2026, Qure.ai received a multimillion-dollar grant from the Bill & Melinda Gates Foundation to develop a large, open-source multimodal database and AI-enabled point-of-care ultrasound algorithms.
• In November 2025, Butterfly Network, Inc. launched Compass AI, an artificial intelligence-powered enterprise platform designed to improve point-of-care ultrasound workflows, documentation, program management, and compliance.

Competitive Landscape

The AI-enabled medical imaging solutions market includes established medical imaging manufacturers and specialized AI companies competing through product launches, regulatory clearances, strategic partnerships, acquisitions, and portfolio expansion. Prominent participants include Agfa-Gevaert Group, Aidoc, Butterfly Network, Inc., Canon Inc., Carestream Health Inc., FUJIFILM Holdings Corporation, General Electric Company, Hologic, Inc., Lunit Inc., Qure.ai, RadNet, Inc. (DeepHealth, Inc.), Koninklijke Philips N.V., Samsung Electronics Co., Ltd, Siemens Healthineers AG, and VUNO, Inc.

The report supports product, innovation, growth, marketing, and competitive planning by identifying high-potential opportunities across products, modalities, workflows, therapeutic applications, deployment models, and regions. Organizations can use the findings to assess market entry options, prioritize customer groups, benchmark competing platforms, identify portfolio gaps, and evaluate partnership or acquisition opportunities.

Market estimates cover 2024 through 2036, with 2025 used as the base year and 2026 to 2036 representing the forecast period. Findings were developed through primary interviews with executives, technology leaders, healthcare institutions, imaging centers, radiology service providers, and solution vendors. Secondary research included company filings, annual reports, investor presentations, product portfolios, recognized publications, industry databases, white papers, journals, press releases, and news sources.

The global AI-enabled medical imaging solutions market is projected to reach $18,356.5 million by 2032, expanding at a CAGR of 25.76% during the 2022-2032 forecast period. Market growth is being driven by rising awareness of early chronic disease detection, demand for greater diagnostic accuracy, and the increasing use of artificial intelligence to support clinical decision-making and improve productivity across medical imaging workflows.

Artificial intelligence is transforming medical imaging through advanced cognitive algorithms that support quantitative imaging, prognostic risk assessment, continuous treatment monitoring, and more accurate diagnoses. As healthcare providers seek efficient technologies capable of managing growing imaging volumes, AI-enabled medical imaging solutions are expected to gain further adoption across multiple modalities and therapeutic applications.

Report Highlights

• Extensive product benchmarking based on modality, workflow, and therapeutic applications, covering established and emerging market participants
• In-depth analysis of key industry developments, competitive strategies, product launches, approvals, partnerships, agreements, and collaborations
• Assessment of the regulatory framework and legal requirements governing AI-enabled medical imaging solutions
• Clinical trials data covering AI-enabled imaging solutions across multiple therapeutic areas
• Cross-segmentation analysis and country-level market estimates
• Evaluation of key market trends, growth opportunities, challenges, and potential revenue areas
• Real-world evidence supported by relevant industry case studies
• Analysis of the industry ecosystem and FDA-approved AI-enabled medical imaging solutions
• Market share analysis, patent filing trends, and funding scenarios
• Regional outlook for North America, Europe, Asia-Pacific, and the Rest-of-the-World (RoW)

Analyst Perspective

According to the report's lead research analyst, artificial intelligence is fundamentally reshaping the medical imaging industry by improving diagnostic accuracy and operational productivity. Emerging cognitive algorithms are creating opportunities in quantitative imaging, prognostic risk assessment, continuous treatment monitoring, and precise clinical interpretation. These capabilities are expected to strengthen the role of AI-enabled imaging technologies in healthcare delivery throughout the forecast period.

Competitive Landscape

The study profiles companies offering AI-enabled medical imaging solutions and compares their products by workflow, modality, and therapeutic application. This benchmarking provides a clear view of how leading and emerging participants are positioned within the global market. The competitive analysis also examines strategic partnerships, agreements, collaborations, product launches, regulatory approvals, and funding activities that may influence future market growth.

Key companies profiled in the report include Agfa-Gevaert Group, Aidoc, Blackford Analysis Limited, Butterfly Network, Inc., Canon Inc., Caption Health, Carestream Health Inc., FUJIFILM Holdings Corporation, General Electric Company, Hologic, Inc., iCAD, Inc., Koninklijke Philips N.V., NVIDIA Corporation, Siemens Healthineers AG, and VUNO, Inc.

Key Market Insights Covered

• Major drivers, challenges, and opportunities affecting the global AI-enabled medical imaging solutions market
• Emerging technology, clinical, regulatory, and commercialization trends
• Forecast growth and revenue potential by product type through 2032
• Regional growth prospects across North America, Europe, Asia-Pacific, and the Rest-of-the-World (RoW)
• Patent filing activity and innovation trends within AI-enabled medical imaging
• Case studies demonstrating clinical and operational applications
• Market segmentation and ranking by imaging modality
• Market segmentation and ranking by therapeutic application
• The impact of the COVID-19 pandemic on adoption, investment, and market development

By combining market forecasts, competitive benchmarking, clinical evidence, regulatory analysis, and country-level data, the report provides stakeholders with a comprehensive view of the global AI-enabled medical imaging solutions market. The findings can support healthcare technology companies, medical imaging providers, investors, policymakers, and other industry participants in evaluating growth strategies and identifying opportunities through 2032.

Key Attributes:

Report Attribute	Details
No. of Pages	181
Forecast Period	2026 - 2036
Estimated Market Value (USD) in 2026	$3.56 Billion
Forecasted Market Value (USD) by 2036	$18.04 Billion
Compound Annual Growth Rate	17.6%
Regions Covered	Global

Key Topics Covered:
Executive Summary
Scope and Definition
1 Global AI-Enabled Medical Imaging Solutions Market: Industry Outlook
1.1 Market Overview
1.2 Market Trends
1.2.1 Impact Analysis
1.2.2 Key Trends
1.2.2.1 Increasing Strategic Collaborations and Partnerships among Industry Stakeholders
1.2.2.2 Advancement Toward Foundation Models and Generative AI Expanding Imaging AI Capabilities
1.2.2.3 Shift toward Cloud- and Web-Based AI Platforms
1.2.2.4 Platformization of AI in Medical Imaging Supporting Multi-Vendor Integration and Orchestration
1.2.3 Opportunity Assessment
1.3 Regulatory Framework
1.3.1 Consortiums, Associations, and Regulatory Bodies
1.3.2 Regulatory Framework for Artificial Intelligence-Based FDA-Approved Medical Devices and Algorithms
1.3.3 Regulatory Framework in North America
1.3.3.1 Regulatory Framework in the U.S.
1.3.4 Regulatory Framework in Europe
1.3.5 Regulatory Framework in Asia-Pacific
1.3.5.1 Regulatory Framework in Japan
1.3.5.2 Regulatory Framework in China
1.3.5.3 Regulatory Framework in India
1.3.6 Regulatory Framework in the Other Countries
1.3.6.1 Regulatory Framework in Brazil
1.3.6.2 Regulatory Framework in Mexico
1.3.6.3 Regulatory Framework in Israel
1.3.6.4 Regulatory Framework in the K.S.A.
1.3.6.5 Regulatory Framework in the U.A.E.
1.4 Value Chain Analysis
1.4.1 Key Stages in Value Chain
1.4.2 Key Challenges across the Value Chain
1.4.3 Strategic Implications for Stakeholders
1.5 Market Dynamics
1.5.1 Drivers, Challenges, and Opportunities: Current and Future Impact Assessment
1.5.2 Market Drivers
1.5.2.1 Growing Emphasis on Early Detection and Risk-Based Screening Driving Adoption of AI-Enabled Medical Imaging Solutions
1.5.2.2 Need for Improved Diagnostic Accuracy and Clinical Decision-Making Accelerating AI Integration in Medical Imaging
1.5.2.3 Expansion of Multi-Specialty and Multi-Modality Clinical Applications Increasing Demand for AI Medical Imaging Solutions
1.5.2.4 Technological Advancements Enabling Higher-Value AI Imaging Capabilities
1.5.3 Market Challenges
1.5.3.1 Legal and Liability-Related Concerns Limiting Adoption of AI-Enabled Medical Imaging Solutions
1.5.3.2 Increasing Cybersecurity Risks and Data Privacy Constraints Restricting Scalable AI Deployment in Medical Imaging
1.5.4 Market Opportunities
1.5.4.1 Shortage of Healthcare Workforce Creating Opportunities for AI-Based Workflow Augmentation
1.5.4.2 Expanding Healthcare Infrastructure and Digital Transformation Creating Growth Opportunities in Emerging Economies
1.5.4.3 Advancements in Real-Time and Edge AI Creating New Opportunities for Intelligent Imaging Devices
2 Global AI-Enabled Medical Imaging Solutions Market (by Product), $Million, 2024-2036
Each product segment includes an overview, market sizing, and forecast.
2.1 Software
2.2 Hardware
3 Global AI-Enabled Medical Imaging Solutions Market (by Modality), $Million, 2024-2036
Each modality segment includes an overview, market sizing, and forecast.
3.1 Computed Tomography
3.2 Magnetic Resonance Imaging
3.3 Ultrasound
3.4 X-Ray
3.5 Others
4 Global AI-Enabled Medical Imaging Solutions Market (by Deployment Model), $Million, 2024-2036
Each deployment model includes an overview, market sizing, and forecast.
4.1 Cloud- and Web-Based Solutions
4.2 On-Premises Solutions
5 Global AI-Enabled Medical Imaging Solutions Market (by Workflow), $Million, 2024-2036
Each workflow segment includes an overview, market sizing, and forecast.
5.1 Image Acquisition
5.2 Image Analysis
5.3 Detection
5.4 Diagnosis and Treatment Decision Support
5.5 Predictive Analysis and Risk Assessment
5.6 Triage
5.7 Reporting and Communication
6 Global AI-Enabled Medical Imaging Solutions Market (by Application), $Million, 2024-2036
Each application segment includes an overview, market sizing, and forecast.
6.1 Specialty Imaging
6.1.1 Cardiology
6.1.2 Oncology
6.1.2.1 Lung Cancer
6.1.2.2 Breast Cancer
6.1.2.3 Other Cancer Types
6.1.3 Neurology
6.1.4 Respiratory
6.1.5 Orthopedics
6.1.6 Others
6.2 General Imaging
7 Global AI-Enabled Medical Imaging Solutions Market (by Region), $Million, 2024-2036
Each regional and country-level assessment includes an overview, growth drivers, market challenges, analyst view, market sizing, and forecast.
7.1 North America
7.1.1 U.S.
7.1.2 Canada
7.2 Europe
7.2.1 U.K.
7.2.2 Germany
7.2.3 France
7.2.4 Italy
7.2.5 Spain
7.2.6 Switzerland
7.2.7 Sweden
7.2.8 Netherlands
7.2.9 Rest-of-Europe
7.3 Asia-Pacific
7.3.1 China
7.3.2 Japan
7.3.3 Australia and New Zealand
7.3.4 South Korea
7.3.5 Singapore
7.3.6 Rest-of-Asia-Pacific
7.4 Rest-of-the-World
7.4.1 Israel
7.4.2 Brazil
7.4.3 Mexico
7.4.4 Rest-of-Rest-of-the-World
8 Competitive Benchmarking and Company Profiles
8.1 Key Strategies and Developments, January 2023-March 2026
8.2 Key Developments Analysis (by Company)
8.3 Company Profiles
Each company profile covers the company overview, top products/product portfolio, top competitors, target customers, key personnel, and analyst view.
8.3.1 Agfa-Gevaert Group
8.3.2 Aidoc
8.3.3 Butterfly Network, Inc.
8.3.4 Canon Inc.
8.3.5 Carestream Health Inc.
8.3.6 FUJIFILM Holdings Corporation
8.3.7 General Electric Company
8.3.8 Hologic, Inc.
8.3.9 Lunit Inc.
8.3.10 Qure.ai
8.3.11 RadNet, Inc. (DeepHealth, Inc.)
8.3.12 Koninklijke Philips N.V.
8.3.13 Samsung Electronics Co., Ltd
8.3.14 Siemens Healthineers AG
8.3.15 VUNO, Inc.
9 Research Methodology
9.1 Data Sources
9.1.1 Primary Data Sources
9.1.2 Secondary Data Sources
9.1.3 Data Triangulation
9.2 Market Estimation and Forecast
Companies Featured

• Agfa-Gevaert Group
• Aidoc
• Butterfly Network, Inc.
• Canon Inc.
• Carestream Health Inc.
• FUJIFILM Holdings Corporation
• General Electric Company
• Hologic, Inc.
• Lunit Inc.
• Qure.ai
• RadNet, Inc.
• Koninklijke Philips N.V.
• Samsung Electronics Co., Ltd
• Siemens Healthineers AG
• VUNO, Inc.

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