AI 기반 의료 영상 솔루션 시장 - 세계 및 지역별 분석 : 모달리티, 제품, 전개 모델, 워크플로우, 용도, 지역별, 분석 및 예측(2026-2036년)

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Introduction of the AI-Enabled Medical Imaging Solutions Market

The global AI-enabled medical imaging solutions market, initially valued at $2,587.3 million in 2024, is projected to grow substantially, reaching $18,041.3 million by 2036, with a remarkable compound annual growth rate (CAGR) of 17.60% from 2026 to 2036.

The global AI-enabled medical imaging solutions market is witnessing significant growth, driven by the increasing demand for faster, more accurate, and workflow-efficient diagnostic imaging across healthcare systems. AI-enabled medical imaging solutions involve the integration of artificial intelligence algorithms with imaging modalities such as X-ray, Magnetic Resonance Imaging (MRI) Systems, Computed Tomography, ultrasound, along with other imaging modalities to support image acquisition, reconstruction, analysis, interpretation, triage, and reporting. These solutions are increasingly being adopted to improve diagnostic accuracy, reduce reporting turnaround time, enhance radiologist productivity, and support early disease detection across high-burden clinical areas such as oncology, cardiology, neurology, pulmonology, and musculoskeletal disorders. The market is expanding as healthcare providers face rising imaging volumes, radiologist shortages, and growing pressure to deliver timely and consistent diagnostic outcomes. AI-enabled solutions assist clinicians by automating repetitive tasks, detecting abnormalities, prioritizing critical cases, and improving image quality while potentially reducing scan time and radiation exposure.

Technological advancements are reshaping the AI-enabled medical imaging landscape, with innovations such as deep learning-based image reconstruction, computer-aided detection, predictive analytics, automated segmentation, and generative AI-assisted reporting improving the efficiency and clinical value of imaging workflows. Key market players are actively developing modality-specific and disease-specific AI applications, while partnerships between imaging vendors, AI software companies, hospitals, and research institutions are accelerating product development and commercialization. Despite strong growth prospects, the market continues to face challenges such as regulatory complexity, data privacy concerns, interoperability issues, algorithm validation requirements, and the need for seamless clinical integration. However, increasing regulatory approvals, growing investment in digital health infrastructure, and the rising acceptance of AI-assisted diagnostics are expected to support continued market expansion over the forecast period.

Market Introduction

The global AI-enabled medical imaging solutions market has undergone a significant transformation, driven by the rapid integration of artificial intelligence across diagnostic imaging workflows and the growing need for faster, more accurate, and scalable radiology solutions. Companies are increasingly incorporating advanced technologies such as deep learning, machine learning, computer-aided detection, automated image reconstruction, and AI-assisted reporting to improve the speed, accuracy, and consistency of medical image interpretation. These solutions are being applied across key imaging modalities, including X-ray, CT, MRI, ultrasound, and other modalities, supporting clinicians in disease detection, workflow optimization, triage, and treatment planning.

Noteworthy advancements, such as AI-based image enhancement, automated lesion detection, organ segmentation, predictive analytics, and generative AI-enabled reporting, highlight the industry's focus on improving diagnostic efficiency and reducing the burden on radiologists. As imaging volumes continue to rise and healthcare systems face persistent radiology workforce shortages, AI-enabled medical imaging solutions are becoming increasingly important in supporting timely diagnosis and clinical decision-making. With growing adoption across hospitals, diagnostic imaging centers, and ambulatory care settings, these technologies are expected to shape the market's trajectory, positioning AI as a central component of next-generation medical imaging and precision healthcare delivery.

Industrial Impact

The global AI-enabled medical imaging solutions market has witnessed substantial growth, driven by the increasing demand for efficient, high-accuracy, and workflow-integrated diagnostic imaging solutions. Key players such as Agfa-Gevaert Group, Carestream Health, Inc., FUJIFILM Holdings Corporation, General Electric Company, Koninklijke Philips N.V., and Siemens Healthineers AG are playing a pivotal role in advancing AI-driven imaging technologies. These companies are actively developing and integrating AI capabilities across imaging workflows, including image acquisition optimization, automated abnormality detection, triage, diagnosis support, image reconstruction, and reporting assistance. These innovations are particularly impactful in high-burden clinical areas such as oncology, cardiology, neurology, pulmonology, breast imaging, trauma assessment, and musculoskeletal diagnostics, where rapid and accurate image interpretation is critical. AI-enabled medical imaging solutions are enhancing diagnostic consistency, reducing reporting turnaround times, improving radiologist productivity, and supporting earlier detection of clinically significant abnormalities. The integration of AI into enterprise imaging platforms, PACS/RIS systems, and cloud-based deployment models is further enabling scalable adoption across healthcare facilities.

Market Segmentation:

Segmentation 1: By Product

• Hardware
• Software

Software Segment to Dominate the AI-Enabled Medical Imaging Solutions Market (by Product)

On the basis of product, the software segment is expected to hold the largest share in the global AI-enabled medical imaging solutions market. This is primarily due to the increasing use of AI-based software for image analysis, detection, triage, workflow automation, reporting, image reconstruction, and clinical decision support. AI software can be deployed across existing imaging systems, allowing healthcare providers to enhance diagnostic workflows without immediately replacing installed imaging equipment.

Segmentation 2: By Modality

• X-Ray
• Ultrasound
• Magnetic Resonance Imaging
• Computed Tomography
• Others

Computed Tomography Segment to Dominate the AI-Enabled Medical Imaging Solutions Market (by Modality)

On the basis of modality, the computed tomography segment is expected to hold the largest share in the global AI-enabled medical imaging solutions market. This dominance is primarily driven by the high utilization of CT imaging across oncology, cardiology, neurology, pulmonology, trauma, and emergency care pathways. CT is widely used for disease detection, staging, treatment planning, follow-up assessment, and acute diagnosis, making it one of the most commercially relevant modalities for AI integration. AI-enabled CT solutions are increasingly being adopted for image reconstruction, lesion detection, organ segmentation, triage, workflow optimization, dose reduction, and quantitative image analysis. These solutions help radiologists manage large imaging volumes, improve diagnostic consistency, and accelerate reporting turnaround times.

Segmentation 3: By Deployment Model

• Cloud- and Web-Based Solutions
• On-Premise Solutions

On-Premises Solutions to Dominate the AI-Enabled Medical Imaging Solutions Market (by Deployment Model)

Based on the deployment model, on-premises solutions are expected to hold the largest share of the AI-enabled medical imaging solutions market. This is mainly due to hospitals' preference for data security, regulatory control, cybersecurity management, and direct integration with existing PACS, RIS, enterprise imaging, and hospital IT infrastructure. Large hospitals and academic medical centers often manage high volumes of sensitive imaging data and therefore prefer deployment models that allow greater control over data storage, processing, access, and compliance.

Segmentation 4: By Workflow

• Image Acquisition
• Image Analysis
• Detection
• Diagnosis and Treatment Decision Support
• Predictive Analysis and Risk Assessment
• Triage
• Reporting and Communication

Image Analysis to Dominate the AI-Enabled Medical Imaging Solutions Market (by Workflow)

Based on workflow, the image analysis segment is expected to capture the largest share of the global AI-enabled medical imaging solutions market. Image analysis forms the core functional layer of AI adoption across different modalities. It enables the extraction of clinically meaningful insights from medical images through image enhancement, reconstruction, segmentation, quantification, anatomical recognition, abnormality characterization, and workflow optimization. The dominance of this segment is supported by its broad applicability across multiple clinical areas, including oncology, cardiology, neurology, musculoskeletal imaging, women's health, and emergency care. AI-powered image analysis solutions help reduce variability in interpretation, support radiologists in identifying subtle abnormalities, and improve the consistency and speed of diagnostic workflows.

Segmentation 5: By Therapeutic Application

• General Imaging
• Specialty Imaging

Specialty Imaging to Dominate the AI-Enabled Medical Imaging Solutions Market (by Therapeutic Application)

Based on therapeutic applications, specialty imaging is expected to hold the largest share in the global AI-enabled medical imaging solutions market. This is driven by the higher revenue contribution of AI-enabled CT, MRI, and advanced imaging systems used in complex clinical areas such as oncology, cardiology, neurology, and other specialty care pathways. Specialty imaging requires advanced capabilities such as lesion detection, anatomical segmentation, image quantification, treatment planning, disease progression monitoring, and clinical decision support.

Segmentation 6: By Region

• North America
  • U.S.
  • Canada
• Europe
  • U.K.
  • Germany
  • France
  • Italy
  • Spain
  • Switzerland
  • Sweden
  • Netherlands
  • Rest-of-Europe
• Asia-Pacific
  • China
  • Japan
  • Australia and New Zealand
  • South Korea
  • Singapore
  • Rest-of-Asia-Pacific
• Rest-of-the-World

North America to Dominate the AI-Enabled Medical Imaging Solutions Market (by Region)

On the basis of region, North America is expected to hold the largest share in the global AI-enabled medical imaging solutions market. This leadership is mainly due to the region's advanced healthcare infrastructure, high adoption of digital imaging technologies, strong presence of AI imaging companies, better purchasing capacity, and faster integration of AI tools across radiology workflows. The U.S. also has a large installed base of CT, MRI, X-ray, and ultrasound systems, which supports faster commercialization and deployment of AI-enabled imaging solutions.

Recent Developments in the AI-Enabled Medical Imaging Solutions Market

• In March 2026, NVIDIA Corporation partnered with global robotics leaders to advance AI-enabled physical intelligence platforms, accelerating real-world deployment of AI-driven imaging, perception, and decision-making systems across industries, including healthcare, where imaging-based AI supports automation and precision diagnostics.
• In January 2026, Qure.ai announced it had 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. announced the launch of Compass AI, an artificial intelligence-powered enterprise software platform designed to optimize point-of-care ultrasound (POCUS) program management through enhanced workflows, documentation, and compliance.

Demand - Drivers, Challenges, and Opportunities

Market Drivers:

Growing Emphasis on Early Detection and Risk-Based Screening Driving Adoption of AI-Enabled Medical Imaging Solutions: The global AI-enabled medical imaging solutions market is being driven by the growing focus on early detection, risk-based screening, and timely diagnosis of cancer and other chronic diseases. Healthcare systems are increasingly prioritizing screening and early diagnosis to improve patient outcomes, reduce disease progression, and lower downstream treatment burden. AI-enabled imaging tools are supporting this shift by assisting radiologists in automated detection, triage, risk stratification, diagnostic decision support, and workflow prioritization across modalities such as chest X-ray, CT, and MRI. Public screening initiatives, imaging data infrastructure programs, and growing clinical validation of AI-assisted tools are further strengthening adoption. As healthcare providers move toward population-level screening and opportunistic detection, AI-enabled medical imaging solutions are increasingly being positioned as important tools for improving diagnostic efficiency, enabling earlier intervention, and supporting more scalable imaging workflows.

Market Challenges:

Legal and Liability-Related Concerns Limiting Adoption of AI-Enabled Medical Imaging Solutions: Legal and liability-related concerns remain a key challenge for the adoption of AI-enabled medical imaging solutions, particularly as these tools become more deeply integrated into clinical workflows. While most current solutions are designed to support radiologists and clinicians, uncertainty remains regarding accountability when AI-assisted outputs contribute to missed findings, false positives, delayed diagnoses, or inappropriate clinical decisions. The absence of clearly defined responsibility among clinicians, healthcare institutions, and software vendors creates hesitation among providers, especially in high-risk areas such as oncology, neurology, and emergency imaging. In addition, concerns related to informed consent, data privacy, algorithmic bias, model transparency, and the black-box nature of deep learning systems further affect clinical trust and medico-legal confidence. As a result, many healthcare organizations continue to deploy AI primarily as an assistive tool rather than relying on it for autonomous decision-making, which can slow broader adoption and limit the full commercial potential of AI-enabled medical imaging solutions.

Market Opportunities:

Shortage of Healthcare Workforce Creating Opportunities for AI-Based Workflow Augmentation: The global shortage of healthcare professionals is creating strong opportunities for AI-enabled medical imaging solutions, particularly as imaging volumes continue to rise while the availability of radiologists, radiographers, and imaging technologists remains constrained. Healthcare systems are facing increasing pressure from growing chronic disease burden, aging populations, expanding screening programs, and higher demand for timely diagnostic interpretation. This imbalance is contributing to heavier radiology workloads, longer reporting turnaround times, and delays in clinical decision-making. AI-enabled medical imaging solutions can help address these challenges by supporting image analysis, case triage, workflow prioritization, reporting assistance, and quality improvement. Rather than replacing clinical expertise, AI acts as an augmentation tool that reduces repetitive manual tasks, improves productivity, and enables more consistent interpretation across high-volume imaging settings. This creates a significant market opportunity, especially for hospitals and diagnostic centers seeking scalable solutions to improve efficiency despite workforce limitations.

How can this report add value to an organization?

Product/Innovation Strategy: The global AI-enabled medical imaging solutions market has been segmented across key areas such as workflow, modality, application, deployment model, and region. By understanding which segments hold the largest market share and which areas are expected to grow rapidly, this report helps organizations identify high-potential opportunities for product development, AI algorithm expansion, workflow integration, and modality-specific innovation. It also supports companies in aligning their solutions with evolving clinical needs across image acquisition, analysis, triage, reporting, and decision support.

Growth/Marketing Strategy: Strategic partnerships, collaborations, product launches, regulatory clearances, and geographic expansion are expected to play a central role in the growth of the AI-enabled medical imaging solutions market. Collaborations between imaging vendors, AI software developers, hospitals, cloud platform providers, and research institutions are strengthening the commercialization and clinical validation of AI-enabled imaging tools. This report helps organizations assess market entry opportunities, prioritize target customer groups, and develop growth strategies across hospitals, diagnostic imaging centers, and enterprise imaging platforms.

Competitive Strategy: The AI-enabled medical imaging solutions market is becoming increasingly competitive, with established imaging companies and specialized AI vendors actively developing solutions across multiple modalities and disease areas. Key players are focusing on AI-based detection, workflow automation, image reconstruction, reporting support, and cloud-based deployment to differentiate their offerings. This report supports organizations in benchmarking competitors, understanding product positioning, identifying strategic gaps, and evaluating opportunities for partnerships, acquisitions, and portfolio expansion in the evolving AI-enabled medical imaging ecosystem.

Methodology

Key Considerations and Assumptions in Market Engineering and Validation

• Years from 2024 to 2036 have been considered for the global market size estimation, 2025 has been considered as the base year, and 2026 to 2036 as the forecast period.
• The scope of the report is based on comprehensive inputs from industry experts across various sectors, including specialty clinics and hospitals, diagnostic laboratories, imaging centers, reference laboratories, and research institutions.
• The market contribution of AI-enabled medical imaging solutions is anticipated to grow substantially in the future, with projections based on historical analysis of available solutions.
• Revenues from companies have been sourced from their annual reports for FY2024 and FY2025. For private companies, revenue estimates are derived from primary research inputs, funding history, market collaborations, and operational performance.
• The market has been mapped based on the existing AI-enabled medical imaging software and hardware. Key companies with significant offerings in this field have been identified and profiled in this report.

Primary Research

The primary sources involve industry experts and key stakeholders across the healthcare and medical imaging ecosystem, including AI-enabled imaging solution providers, medical device manufacturers, radiology service providers, and healthcare institutions. Stakeholders such as hospitals, imaging centers, and teleradiology providers have been consulted to validate adoption trends and clinical utility. Respondents, including CEOs, vice presidents, product and marketing directors, and technology and innovation leaders, have been interviewed to obtain and verify both qualitative and quantitative insights for this research study.

The key data points taken from the primary sources include:

• validation and triangulation of all the numbers and graphs
• validation of report segmentations and key qualitative findings
• understanding the competitive landscape and business model
• current and proposed production values of a product by market players
• validation of the numbers of different segments of the market in focus
• percentage split of individual markets for regional analysis

Secondary Research

Open Sources

• Certified publications, articles from recognized authors, white papers, directories, and major databases, among others
• Annual reports, SEC filings, and investors' presentations of the leading market players
• Company websites and a detailed study of their product portfolio
• Gold standard magazines, journals, white papers, press releases, and news articles
• Paid databases

The key data points taken from the secondary sources include:

• segmentations and percentage shares
• data for market value
• key industry trends of the top players in the market
• qualitative insights into various aspects of the market, key trends, and emerging areas of innovation
• quantitative data for mathematical and statistical calculations

Key Market Players and Competition Synopsis

The companies profiled have been selected based on inputs gathered from an analysis of company coverage, product portfolio, and market penetration.

Some prominent names established in this market are:

• 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
• VUNO, Inc.

Table of Contents

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

• 2.1 Software
  • 2.1.1 Overview
  • 2.1.2 Market Sizing and Forecast
• 2.2 Hardware
  • 2.2.1 Overview
  • 2.2.2 Market Sizing and Forecast

3 Global AI-Enabled Medical Imaging Solutions Market (by Modality), $Million, 2024-2036

• 3.1 Computed Tomography
  • 3.1.1 Overview
  • 3.1.2 Market Sizing and Forecast
• 3.2 Magnetic Resonance Imaging
  • 3.2.1 Overview
  • 3.2.2 Market Sizing and Forecast
• 3.3 Ultrasound
  • 3.3.1 Overview
  • 3.3.2 Market Sizing and Forecast
• 3.4 X-Ray
  • 3.4.1 Overview
  • 3.4.2 Market Sizing and Forecast
• 3.5 Others
  • 3.5.1 Overview
  • 3.5.2 Market Sizing and Forecast

4 Global AI-Enabled Medical Imaging Solutions Market (by Deployment Model), $Million, 2024-2036

• 4.1 Cloud- and Web-Based Solutions
  • 4.1.1 Overview
  • 4.1.2 Market Sizing and Forecast
• 4.2 On-Premises Solutions
  • 4.2.1 Overview
  • 4.2.2 Market Sizing and Forecast

5 Global AI-Enabled Medical Imaging Solutions Market (by Workflow), $Million, 2024-2036

• 5.1 Image Acquisition
  • 5.1.1 Overview
  • 5.1.2 Market Sizing and Forecast
• 5.2 Image Analysis
  • 5.2.1 Overview
  • 5.2.2 Market Sizing and Forecast
• 5.3 Detection
  • 5.3.1 Overview
  • 5.3.2 Market Sizing and Forecast
• 5.4 Diagnosis and Treatment Decision Support
  • 5.4.1 Overview
  • 5.4.2 Market Sizing and Forecast
• 5.5 Predictive Analysis and Risk Assessment
  • 5.5.1 Overview
  • 5.5.2 Market Sizing and Forecast
• 5.6 Triage
  • 5.6.1 Overview
  • 5.6.2 Market Sizing and Forecast
• 5.7 Reporting and Communication
  • 5.7.1 Overview
  • 5.7.2 Market Sizing and Forecast

6 Global AI-Enabled Medical Imaging Solutions Market (by Application), $Million, 2024-2036

• 6.1 Specialty Imaging
  • 6.1.1 Overview
  • 6.1.2 Market Sizing and Forecast
    • 6.1.2.1 Cardiology
    • 6.1.2.2 Oncology
      • 6.1.2.2.1 Lung Cancer
      • 6.1.2.2.2 Breast Cancer
      • 6.1.2.2.3 Other Cancer Types
    • 6.1.2.3 Neurology
    • 6.1.2.4 Respiratory
    • 6.1.2.5 Orthopedics
    • 6.1.2.6 Others
• 6.2 General Imaging
  • 6.2.1 Overview
  • 6.2.2 Market Sizing and Forecast

7 Global AI-Enabled Medical Imaging Solutions Market (by Region), $Million, 2024-2036

• 7.1 North America
  • 7.1.1 Regional Overview
  • 7.1.2 Driving Factors for Market Growth
  • 7.1.3 Factors Challenging the Market
  • 7.1.4 Analyst View
  • 7.1.5 Market Sizing and Forecast
    • 7.1.5.1 North America AI-Enabled Medical Imaging Solutions Market, by Country
      • 7.1.5.1.1 U.S.
        • 7.1.5.1.1.1 Country Overview
        • 7.1.5.1.1.2 Driving Factors for Market Growth
        • 7.1.5.1.1.3 Factors Challenging the Market
        • 7.1.5.1.1.4 Analyst View
        • 7.1.5.1.1.5 Market Sizing and Forecast
      • 7.1.5.1.2 Canada
        • 7.1.5.1.2.1 Country Overview
        • 7.1.5.1.2.2 Driving Factors for Market Growth
        • 7.1.5.1.2.3 Factors Challenging the Market
        • 7.1.5.1.2.4 Analyst View
        • 7.1.5.1.2.5 Market Sizing and Forecast
• 7.2 Europe
  • 7.2.1 Regional Overview
  • 7.2.2 Driving Factors for Market Growth
  • 7.2.3 Factors Challenging the Market
  • 7.2.4 Analyst View
  • 7.2.5 Market Sizing and Forecast
    • 7.2.5.1 Europe AI-Enabled Medical Imaging Solutions Market, by Country
      • 7.2.5.1.1 U.K.
        • 7.2.5.1.1.1 Country Overview
        • 7.2.5.1.1.2 Driving Factors for Market Growth
        • 7.2.5.1.1.3 Factors Challenging the Market
        • 7.2.5.1.1.4 Analyst View
        • 7.2.5.1.1.5 Market Sizing and Forecast
      • 7.2.5.1.2 Germany
        • 7.2.5.1.2.1 Country Overview
        • 7.2.5.1.2.2 Driving Factors for Market Growth
        • 7.2.5.1.2.3 Factors Challenging the Market
        • 7.2.5.1.2.4 Analyst View
        • 7.2.5.1.2.5 Market Sizing and Forecast
      • 7.2.5.1.3 France
        • 7.2.5.1.3.1 Country Overview
        • 7.2.5.1.3.2 Driving Factors for Market Growth
        • 7.2.5.1.3.3 Factors Challenging the Market
        • 7.2.5.1.3.4 Analyst View
        • 7.2.5.1.3.5 Market Sizing and Forecast
      • 7.2.5.1.4 Italy
        • 7.2.5.1.4.1 Country Overview
        • 7.2.5.1.4.2 Driving Factors for Market Growth
        • 7.2.5.1.4.3 Factors Challenging the Market
        • 7.2.5.1.4.4 Analyst View
        • 7.2.5.1.4.5 Market Sizing and Forecast
      • 7.2.5.1.5 Spain
        • 7.2.5.1.5.1 Country Overview
        • 7.2.5.1.5.2 Driving Factors for Market Growth
        • 7.2.5.1.5.3 Factors Challenging the Market
        • 7.2.5.1.5.4 Analyst View
        • 7.2.5.1.5.5 Market Sizing and Forecast
      • 7.2.5.1.6 Switzerland
        • 7.2.5.1.6.1 Country Overview
        • 7.2.5.1.6.2 Driving Factors for Market Growth
        • 7.2.5.1.6.3 Factors Challenging the Market
        • 7.2.5.1.6.4 Analyst View
        • 7.2.5.1.6.5 Market Sizing and Forecast
      • 7.2.5.1.7 Sweden
        • 7.2.5.1.7.1 Country Overview
        • 7.2.5.1.7.2 Driving Factors for Market Growth
        • 7.2.5.1.7.3 Factors Challenging the Market
        • 7.2.5.1.7.4 Analyst View
        • 7.2.5.1.7.5 Market Sizing and Forecast
      • 7.2.5.1.8 Netherlands
        • 7.2.5.1.8.1 Country Overview
        • 7.2.5.1.8.2 Driving Factors for Market Growth
        • 7.2.5.1.8.3 Factors Challenging the Market
        • 7.2.5.1.8.4 Analyst View
        • 7.2.5.1.8.5 Market Sizing and Forecast
      • 7.2.5.1.9 Rest-of-Europe
        • 7.2.5.1.9.1 Country Overview
        • 7.2.5.1.9.2 Driving Factors for Market Growth
        • 7.2.5.1.9.3 Factors Challenging the Market
        • 7.2.5.1.9.4 Analyst View
        • 7.2.5.1.9.5 Market Sizing and Forecast
• 7.3 Asia-Pacific
  • 7.3.1 Regional Overview
  • 7.3.2 Driving Factors for Market Growth
  • 7.3.3 Factors Challenging the Market
  • 7.3.4 Analyst View
  • 7.3.5 Market Sizing and Forecast
    • 7.3.5.1 Asia-Pacific AI-Enabled Medical Imaging Solutions Market, by Country
      • 7.3.5.1.1 China
        • 7.3.5.1.1.1 Country Overview
        • 7.3.5.1.1.2 Driving Factors for Market Growth
        • 7.3.5.1.1.3 Factors Challenging the Market
        • 7.3.5.1.1.4 Analyst View
        • 7.3.5.1.1.5 Market Sizing and Forecast
      • 7.3.5.1.2 Japan
        • 7.3.5.1.2.1 Country Overview
        • 7.3.5.1.2.2 Driving Factors for Market Growth
        • 7.3.5.1.2.3 Factors Challenging the Market
        • 7.3.5.1.2.4 Analyst View
        • 7.3.5.1.2.5 Market Sizing and Forecast
      • 7.3.5.1.3 Australia and New Zealand
        • 7.3.5.1.3.1 Country Overview
        • 7.3.5.1.3.2 Driving Factors for Market Growth
        • 7.3.5.1.3.3 Factors Challenging the Market
        • 7.3.5.1.3.4 Analyst View
        • 7.3.5.1.3.5 Market Sizing and Forecast
      • 7.3.5.1.4 South Korea
        • 7.3.5.1.4.1 Country Overview
        • 7.3.5.1.4.2 Driving Factors for Market Growth
        • 7.3.5.1.4.3 Factors Challenging the Market
        • 7.3.5.1.4.4 Analyst View
        • 7.3.5.1.4.5 Market Sizing and Forecast
      • 7.3.5.1.5 Singapore
        • 7.3.5.1.5.1 Country Overview
        • 7.3.5.1.5.2 Driving Factors for Market Growth
        • 7.3.5.1.5.3 Factors Challenging the Market
        • 7.3.5.1.5.4 Analyst View
        • 7.3.5.1.5.5 Market Sizing and Forecast
      • 7.3.5.1.6 Rest-of-Asia-Pacific
        • 7.3.5.1.6.1 Country Overview
        • 7.3.5.1.6.2 Driving Factors for Market Growth
        • 7.3.5.1.6.3 Factors Challenging the Market
        • 7.3.5.1.6.4 Analyst View
        • 7.3.5.1.6.5 Market Sizing and Forecast
• 7.4 Rest-of-the-World
  • 7.4.1 Regional Overview
  • 7.4.2 Driving Factors for Market Growth
  • 7.4.3 Factors Challenging the Market
  • 7.4.4 Analyst View
  • 7.4.5 Market Sizing and Forecast
    • 7.4.5.1 Rest-of-the-World AI-Enabled Medical Imaging Solutions Market, by Country
      • 7.4.5.1.1 Israel
        • 7.4.5.1.1.1 Regional Overview
        • 7.4.5.1.1.2 Driving Factors for Market Growth
        • 7.4.5.1.1.3 Factors Challenging the Market
        • 7.4.5.1.1.4 Analyst View
        • 7.4.5.1.1.5 Market Sizing and Forecast
      • 7.4.5.1.2 Brazil
        • 7.4.5.1.2.1 Regional Overview
        • 7.4.5.1.2.2 Driving Factors for Market Growth
        • 7.4.5.1.2.3 Factors Challenging the Market
        • 7.4.5.1.2.4 Analyst View
        • 7.4.5.1.2.5 Market Sizing and Forecast
      • 7.4.5.1.3 Mexico
        • 7.4.5.1.3.1 Regional Overview
        • 7.4.5.1.3.2 Driving Factors for Market Growth
        • 7.4.5.1.3.3 Factors Challenging the Market
        • 7.4.5.1.3.4 Analyst View
        • 7.4.5.1.3.5 Market Sizing and Forecast
      • 7.4.5.1.4 Rest-of-Rest-of-the-World
        • 7.4.5.1.4.1 Regional Overview
        • 7.4.5.1.4.2 Driving Factors for Market Growth
        • 7.4.5.1.4.3 Factors Challenging the Market
        • 7.4.5.1.4.4 Analyst View
        • 7.4.5.1.4.5 Market Sizing and Forecast

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
  • 8.3.1 Agfa-Gevaert Group
    • 8.3.1.1 Overview
    • 8.3.1.2 Top Products/Product Portfolio
    • 8.3.1.3 Top Competitors
    • 8.3.1.4 Target Customers
    • 8.3.1.5 Key Personnel
    • 8.3.1.6 Analyst View
  • 8.3.2 Aidoc
    • 8.3.2.1 Overview
    • 8.3.2.2 Top Products/Product Portfolio
    • 8.3.2.3 Top Competitors
    • 8.3.2.4 Target Customers
    • 8.3.2.5 Key Personnel
    • 8.3.2.6 Analyst View
  • 8.3.3 Butterfly Network, Inc.
    • 8.3.3.1 Overview
    • 8.3.3.2 Top Products/Product Portfolio
    • 8.3.3.3 Top Competitors
    • 8.3.3.4 Target Customers
    • 8.3.3.5 Key Personnel
    • 8.3.3.6 Analyst View
  • 8.3.4 Canon Inc.
    • 8.3.4.1 Overview
    • 8.3.4.2 Top Products/Product Portfolio
    • 8.3.4.3 Top Competitors
    • 8.3.4.4 Target Customers
    • 8.3.4.5 Key Personnel
    • 8.3.4.6 Analyst View
  • 8.3.5 Carestream Health Inc.
    • 8.3.5.1 Overview
    • 8.3.5.2 Top Products/Product Portfolio
    • 8.3.5.3 Top Competitors
    • 8.3.5.4 Target Customers
    • 8.3.5.5 Key Personnel
    • 8.3.5.6 Analyst View
  • 8.3.6 FUJIFILM Holdings Corporation
    • 8.3.6.1 Overview
    • 8.3.6.2 Top Products/Product Portfolio
    • 8.3.6.3 Top Competitors
    • 8.3.6.4 Target Customers
    • 8.3.6.5 Key Personnel
    • 8.3.6.6 Analyst View
  • 8.3.7 General Electric Company
    • 8.3.7.1 Overview
    • 8.3.7.2 Top Products/Product Portfolio
    • 8.3.7.3 Top Competitors
    • 8.3.7.4 Target Customers
    • 8.3.7.5 Key Personnel
    • 8.3.7.6 Analyst View
  • 8.3.8 Hologic, Inc.
    • 8.3.8.1 Overview
    • 8.3.8.2 Top Products/Product Portfolio
    • 8.3.8.3 Top Competitors
    • 8.3.8.4 Target Customers
    • 8.3.8.5 Key Personnel
    • 8.3.8.6 Analyst View
  • 8.3.9 Lunit Inc.
    • 8.3.9.1 Overview
    • 8.3.9.2 Top Products/Product Portfolio
    • 8.3.9.3 Top Competitors
    • 8.3.9.4 Target Customers
    • 8.3.9.5 Key Personnel
    • 8.3.9.6 Analyst View
  • 8.3.10 Qure.ai
    • 8.3.10.1 Overview
    • 8.3.10.2 Top Products/Product Portfolio
    • 8.3.10.3 Top Competitors
    • 8.3.10.4 Target Customers
    • 8.3.10.5 Key Personnel
    • 8.3.10.6 Analyst View
  • 8.3.11 RadNet, Inc. (DeepHealth, Inc.)
    • 8.3.11.1 Overview
    • 8.3.11.2 Top Products/Product Portfolio
    • 8.3.11.3 Top Competitors
    • 8.3.11.4 Target Customers
    • 8.3.11.5 Key Personnel
    • 8.3.11.6 Analyst View
  • 8.3.12 Koninklijke Philips N.V.
    • 8.3.12.1 Overview
    • 8.3.12.2 Top Products/Product Portfolio
    • 8.3.12.3 Top Competitors
    • 8.3.12.4 Target Customers
    • 8.3.12.5 Key Personnel
    • 8.3.12.6 Analyst View
  • 8.3.13 Samsung Electronics Co., Ltd
    • 8.3.13.1 Overview
    • 8.3.13.2 Top Products/Product Portfolio
    • 8.3.13.3 Top Competitors
    • 8.3.13.4 Target Customers
    • 8.3.13.5 Key Personnel
    • 8.3.13.6 Analyst View
  • 8.3.14 Siemens Healthineers AG
    • 8.3.14.1 Overview
    • 8.3.14.2 Top Products/Product Portfolio
    • 8.3.14.3 Top Competitors
    • 8.3.14.4 Target Customers
    • 8.3.14.5 Key Personnel
    • 8.3.14.6 Analyst View
  • 8.3.15 VUNO, Inc.
    • 8.3.15.1 Overview
    • 8.3.15.2 Top Products/Product Portfolio
    • 8.3.15.3 Top Competitors
    • 8.3.15.4 Target Customers
    • 8.3.15.5 Key Personnel
    • 8.3.15.6 Analyst View

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