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市场调查报告书
商品编码
2007891

人工智慧医学影像市场预测至2034年—按成像方式、部署模式、技术、应用、最终用户和地区分類的全球分析

AI Medical Imaging Market Forecasts to 2034 - Global Analysis By Modality, Deployment Mode, Technology, Application, End User and Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，预计到 2026 年，全球 AI 医学影像市场规模将达到 56 亿美元，并在预测期内以 22.7% 的复合年增长率增长，到 2034 年将达到 289 亿美元。

人工智慧驱动的医学影像是指将机器学习演算法、深度神经网路和电脑视觉系统应用于医学诊断影像（例如X光片、电脑断层扫描（CT）、磁振造影（MRI）、超音波、核子医学和乳房X光片）的自动化分析、解读和影像增强。这些系统能够侦测解剖结构异常、分割病灶区域、优化放射科医师的工作优先顺序、缩短扫描采集时间并产生结构化的诊断报告。目前，这些系统已在肿瘤科、循环系统、神经科、呼吸内科和整形外科等医院和门诊影像环境中得到应用。

放射科医师短缺及其工作压力巨大。

放射科医生短缺和影像检查数量激增给工作流程带来了巨大压力，但人力智慧医学影像解决方案透过自动化常规影像分流、异常标记和报告，正在应对这一挑战。在大多数大型医疗系统中，影像检查数量的增长速度超过了放射科医生数量的增长速度，导致检查瓶颈，而人工智慧优先排序工具可以很大程度上解决这个问题。医疗系统管理者正在积极采用人工智慧影像解决方案来提高人员效率，这为医学影像人工智慧平台供应商带来了持续的软体订阅收入。

对演算法偏差和普适性的担忧

演算法偏差和泛化能力的限制是临床应用的一大障碍。基于人口统计偏差资料集训练的人工智慧医学影像模型，在应用于训练群组中被低估的患者群体时表现不佳。放射科管理者在决定实施前，越来越倾向于寻求在不同病患群体中进行外部检验的证据。监管机构对人工智慧模型在不同种族、年龄和性别等亚群体中的表现监管力度不断加大，这要求影像人工智慧开发人员投入更多资源进行超越标准临床表现基准的广泛检验研究。

新兴市场的放射学基础设施

新兴市场放射科基础设施的差异为人工智慧驱动的医学影像平台带来了变革性的成长机会，这些平台能够将诊断范围扩展到专科医生集中的都市区之外。人工智慧影像解读工具使农村医疗机构的非专科临床医生能够获得与放射科医生相当的常见疾病诊断结果。印度、东南亚和撒哈拉以南非洲的政府远端医疗和数位健康基础设施项目正在将人工智慧成像功能融入基层医疗服务拓展倡议，从而创造一个巨大的潜在市场。

责任和临床责任方面缺乏明确性

人工智慧驱动的医学影像诊断结果的责任归属和临床责任分割不清，对人工智慧的普及应用构成系统性威胁。这是因为相关法规和法律体制并未明确界定人工智慧诊断错误导致患者预后不良时，应由谁来负责。放射科医师和医院风险负责人对在缺乏独立临床检验的情况下完全依赖人工智慧输出结果持抵制态度，导致人工智慧的自主部署仅限于辅助功能。此外，医疗事故保险对人工智慧辅助诊断的覆盖不足，进一步加剧了机构在加速采用人工智慧过程中面临的风险评估难度。

新冠疫情的影响：

新冠疫情加速了人工智慧在医学影像领域的应用，展现了其在以应对疫情为导向的放射科室中的快速价值，例如，用于检测新冠肺炎的胸部CT和X光人工智慧工具已获得紧急监管核准。疫情期间工作流程自动化的先例巩固了人工智慧影像辅助工具在医院通讯协定的应用。疫情后，随着医疗系统将人工智慧分诊工具永久应用于呼吸系统疾病、肿瘤筛检和心血管影像等领域，人工智慧影像平台的应用正在加速推进。

在预测期内，核医学影像领域预计将占据最大的市场份额。

在预测期内，核医学影像领域预计将占据最大的市场份额。这主要归功于PET-CT和SPECT影像技术在肿瘤分期、心臟灌注评估和神经退化性疾病诊断等领域的临床应用日益广泛。人工智慧（AI）技术与核医学影像的融合，实现了病灶的自动定量、优化的衰减校正以及示踪剂量的降低。越来越多的临床证据表明，人工智慧增强的核子医学扫描术诊断在癌症早期检测方面具有较高的准确性，这促使转诊医生更广泛地应用该技术，并加速了影像中心设备的升级换代。

在预测期内，基于云端的细分市场预计将呈现最高的复合年增长率。

在预测期内，云端解决方案预计将呈现最高的成长率，这主要得益于医疗系统对可扩展人工智慧推理能力的需求，他们希望在无需对本地GPU基础设施进行大量资本投资的情况下获得此类解决方案。云端託管的人工智慧医学影像平台支援多站点部署、持续模型更新以及跨机构资料聚合，从而实现模型的持续改进。领先的云端服务供应商正在建立专用的医学影像人工智慧基础设施和市场生态系统，以降低医院IT部门部署人工智慧诊断工具的整合门槛。

市占率最大的地区：

在预测期内，北美预计将占据最大的市场份额，这得益于其先进的人工智慧医学影像研究基础设施、高诊断影像利用率以及强大的FDA已通过核准人工智慧影像产品产品系列。美国拥有全球最大的人工智慧已通过核准医学影像设备部署基地。强大的先进诊断程序报销机制以及由GE医疗和西门子医疗等公司支持的积极医院人工智慧应用计划，巩固了该地区的领先地位。

复合年增长率最高的地区：

在预测期内，亚太地区预计将呈现最高的复合年增长率，这主要得益于诊断成像基础设施投资的快速成长、政府主导的人工智慧医疗发展项目，以及大量尚未开发的患者群体（他们将受益于人工智慧远距放射学）。中国国家药品监督管理局（NMPA）已建立人工智慧医疗设备的快速审批流程，加速了人工智慧影像产品在国内外市场的核准。日本和韩国的先进影像设备製造生态系统正在将人工智慧功能整合到其所有产品线中。

免费客製化服务：

所有购买此报告的客户均可享受以下免费自订选项之一：

  • 企业概况
    • 对其他市场参与者（最多 3 家公司）进行全面分析
    • 对主要企业进行SWOT分析（最多3家公司）
  • 区域细分
    • 应客户要求，我们提供主要国家和地区的市场估算和预测，以及复合年增长率（註：需进行可行性检查）。
  • 竞争性标竿分析
    • 根据产品系列、地理覆盖范围和策略联盟对主要企业进行基准分析。

目录

第一章执行摘要

  • 市场概览及主要亮点
  • 成长动力、挑战与机会
  • 竞争格局概述
  • 战略洞察与建议

第二章：研究框架

  • 研究目标和范围
  • 相关人员分析
  • 研究假设和限制
  • 调查方法

第三章 市场动态与趋势分析

  • 市场定义与结构
  • 主要市场驱动因素
  • 市场限制与挑战
  • 投资成长机会和重点领域
  • 产业威胁与风险评估
  • 技术与创新展望
  • 新兴市场/高成长市场
  • 监管和政策环境
  • 新冠疫情的影响及復苏前景

第四章：竞争环境与策略评估

  • 波特五力分析
    • 供应商的议价能力
    • 买方的议价能力
    • 替代品的威胁
    • 新进入者的威胁
    • 竞争公司之间的竞争
  • 主要企业市占率分析
  • 产品基准评效和效能比较

第五章：全球人工智慧医学影像市场：以影像方式划分

  • X光影像诊断
  • 电脑断层扫描（CT）
  • 磁振造影（MRI）
  • 超音波影像
  • 核子医学扫描术诊断
  • 乳房X光检查
  • 其他方式

第六章：全球人工智慧医疗影像市场：依部署模式划分

  • 基于云端的
  • 现场
  • 杂交种
  • 网路为基础的平台
  • SaaS模式
  • 整合系统

第七章 全球人工智慧医疗影像市场：按技术划分

  • 深度学习
  • 机器学习
  • 自然语言处理
  • 电脑视觉
  • 基于云端的人工智慧
  • 边缘人工智慧

第八章：全球人工智慧医疗影像市场：按应用领域划分

  • 肿瘤影像诊断
  • 心臟影像
  • 神经影像学
  • 呼吸影像
  • 整形外科影像诊断
  • 消化系统成像
  • 其他用途

第九章：全球人工智慧医疗影像市场：按最终用户划分

  • 医院
  • 诊断影像中心
  • 研究机构
  • 门诊手术中心
  • 远端放射诊断服务供应商
  • 大学医院
  • 其他最终用户

第十章：全球人工智慧医疗影像市场：按地区划分

  • 北美洲
    • 我们
    • 加拿大
    • 墨西哥
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 荷兰
    • 比利时
    • 瑞典
    • 瑞士
    • 波兰
    • 其他欧洲国家
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 韩国
    • 澳洲
    • 印尼
    • 泰国
    • 马来西亚
    • 新加坡
    • 越南
    • 其他亚太国家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥伦比亚
    • 智利
    • 秘鲁
    • 其他南美国家
  • 世界其他地区（RoW）
    • 中东
      • 沙乌地阿拉伯
      • 阿拉伯聯合大公国
      • 卡达
      • 以色列
      • 其他中东国家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲国家

第十一章 策略市场资讯

  • 工业价值网络和供应链评估
  • 空白区域和机会地图
  • 产品演进与市场生命週期分析
  • 通路、经销商和打入市场策略的评估

第十二章 产业趋势与策略倡议

  • 併购
  • 伙伴关係、联盟、合资企业
  • 新产品发布和认证
  • 扩大生产能力和投资
  • 其他策略倡议

第十三章：公司简介

  • GE Healthcare
  • Siemens Healthineers
  • Philips Healthcare
  • Canon Medical Systems Corporation
  • IBM Watson Health
  • Aidoc Medical Ltd.
  • Zebra Medical Vision
  • Arterys Inc.
  • Viz.ai, Inc.
  • Enlitic, Inc.
  • Qure.ai
  • Lunit Inc.
  • Butterfly Network, Inc.
  • Tempus Labs
  • NVIDIA Corporation
  • Fujifilm Holdings Corporation
  • Samsung Medison
  • Agfa-Gevaert Group
Product Code: SMRC34766

According to Stratistics MRC, the Global AI Medical Imaging Market is accounted for $5.6 billion in 2026 and is expected to reach $28.9 billion by 2034 growing at a CAGR of 22.7% during the forecast period. AI medical imaging refers to the application of machine learning algorithms, deep neural networks, and computer vision systems to the automated analysis, interpretation, and enhancement of medical diagnostic images including X-rays, computed tomography scans, magnetic resonance imaging, ultrasound, nuclear medicine, and mammography outputs. These systems detect anatomical anomalies, segment pathological regions, prioritize radiologist worklists, reduce scan acquisition times, and generate structured diagnostic reports. They are deployed in oncology, cardiology, neurology, pulmonology, and orthopedic imaging workflows across hospital and outpatient imaging settings.

Market Dynamics:

Driver:

Radiologist Shortage and Workload Pressure

Radiologist shortage and escalating imaging study volumes are creating acute workflow pressure that AI medical imaging solutions address by automating routine image triage, anomaly flagging, and report generation. Diagnostic imaging volumes are growing faster than radiologist workforce expansion in most major healthcare systems, generating backlogs that AI prioritization tools can materially compress. Health system administrators are actively procuring AI imaging solutions as workforce productivity tools, establishing recurring software subscription revenue streams for medical imaging AI platform vendors.

Restraint:

Algorithm Bias and Generalizability Concerns

Algorithm bias and generalizability limitations present clinical adoption barriers as AI medical imaging models trained on demographically narrow datasets demonstrate performance degradation when applied to patient populations underrepresented in training cohorts. Radiology department administrators are increasingly demanding external validation evidence across diverse patient demographics before procurement commitment. Regulatory scrutiny of AI model performance across racial, age, and gender subgroups is intensifying, requiring extensive validation study investment from imaging AI developers beyond standard clinical performance benchmarks.

Opportunity:

Emerging Market Radiology Infrastructure

Emerging market radiology infrastructure gaps present a transformative growth opportunity for AI medical imaging platforms that can extend diagnostic coverage beyond specialist-concentrated urban centers. AI-powered reading tools enable non-specialist clinicians in rural health facilities to access radiologist-equivalent diagnostic interpretation for common conditions. Government telemedicine and digital health infrastructure programs in India, Southeast Asia, and Sub-Saharan Africa are integrating AI imaging capabilities into primary care expansion initiatives, creating substantial new addressable market volumes.

Threat:

Liability and Clinical Responsibility Ambiguity

Liability and clinical responsibility ambiguity for AI-generated medical imaging interpretations represents a systemic threat to adoption, as regulatory and legal frameworks have not definitively established accountability when AI diagnostic errors contribute to adverse patient outcomes. Radiologists and hospital risk managers express institutional reluctance to fully rely on AI outputs without independent clinical verification, limiting autonomous AI deployment beyond assistive functions. Medical malpractice insurance policy gaps for AI-assisted diagnostics further compound institutional risk calculus against accelerated adoption.

Covid-19 Impact:

COVID-19 catalyzed AI medical imaging adoption as chest CT and X-ray AI tools for COVID-19 pneumonia detection received emergency regulatory approvals, demonstrating rapid value in overwhelmed radiology departments. Pandemic-era workflow automation precedents normalized AI imaging assistant integration in hospital protocols. Post-pandemic, AI imaging platform procurement has accelerated as health systems permanently incorporate AI triage tools for respiratory pathology, oncology screening, and cardiovascular imaging.

The nuclear imaging segment is expected to be the largest during the forecast period

The nuclear imaging segment is expected to account for the largest market share during the forecast period, due to increasing clinical adoption of PET-CT and SPECT imaging for oncology staging, cardiac perfusion assessment, and neurodegenerative disease diagnosis. AI integration with nuclear imaging enables automated lesion quantification, attenuation correction optimization, and reduced tracer dosing protocols. Growing clinical evidence supporting AI-enhanced nuclear imaging accuracy in early cancer detection is expanding referring physician utilization and driving imaging center equipment upgrade cycles.

The cloud-based segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the cloud-based segment is predicted to witness the highest growth rate, driven by health system demand for scalable AI inference capacity without capital-intensive on-premise GPU infrastructure investment. Cloud-hosted AI medical imaging platforms enable multi-site deployment, continuous model update delivery, and cross-institutional data aggregation for ongoing model improvement. Major cloud providers are building dedicated medical imaging AI infrastructure and marketplace ecosystems that reduce integration barriers for hospital IT departments adopting AI diagnostic tools.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to leading AI medical imaging research infrastructure, high diagnostic imaging utilization rates, and substantial FDA-cleared AI imaging product portfolios. The U.S. hosts the largest installed base of medical imaging AI-cleared devices globally. Strong reimbursement frameworks for advanced diagnostic procedures and active hospital AI adoption programs supported by companies including GE Healthcare and Siemens Healthineers sustain dominant regional positioning.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, due to rapidly expanding diagnostic imaging infrastructure investment, government AI healthcare development programs, and large underserved patient populations benefiting from AI-driven teleradiology. China's NMPA has established expedited review tracks for AI medical device approvals, accelerating domestic and international imaging AI product launches. Japan and South Korea's advanced imaging equipment manufacturing ecosystems are integrating AI capabilities across product lines.

Key players in the market

Some of the key players in AI Medical Imaging Market include GE Healthcare, Siemens Healthineers, Philips Healthcare, Canon Medical Systems Corporation, IBM Watson Health, Aidoc Medical Ltd., Zebra Medical Vision, Arterys Inc., Viz.ai, Inc., Enlitic, Inc., Qure.ai, Lunit Inc., Butterfly Network, Inc., Tempus Labs, NVIDIA Corporation, Fujifilm Holdings Corporation, Samsung Medison, and Agfa-Gevaert Group.

Key Developments:

In March 2026, NVIDIA Corporation introduced a purpose-built medical imaging AI inference hardware platform optimized for hospital on-premise deployment with HIPAA-compliant data processing.

In February 2026, GE Healthcare launched its Edison AI imaging platform expansion with new oncology CT lesion detection algorithms cleared by FDA for lung nodule screening workflows.

In January 2026, Aidoc Medical Ltd. secured a major multi-site hospital system contract deploying its AI radiology triage platform across 40 imaging centers for emergency pathology detection.

In October 2025, Qure.ai announced expansion into Latin American markets through a regional telemedicine partnership integrating AI chest X-ray reading into primary care networks.

Modalities Covered:

  • X-ray Imaging
  • Computed Tomography (CT)
  • Magnetic Resonance Imaging (MRI)
  • Ultrasound Imaging
  • Nuclear Imaging
  • Mammography
  • Other Modalities

Deployment Modes Covered:

  • Cloud-based
  • On-premise
  • Hybrid
  • Web-based Platforms
  • SaaS Models
  • Integrated Systems

Technologies Covered:

  • Deep Learning
  • Machine Learning
  • Natural Language Processing
  • Computer Vision
  • Cloud-based AI
  • Edge AI

Applications Covered:

  • Oncology Imaging
  • Cardiology Imaging
  • Neurology Imaging
  • Pulmonology Imaging
  • Orthopedic Imaging
  • Gastroenterology Imaging
  • Other Applications

End Users Covered:

  • Hospitals
  • Diagnostic Imaging Centers
  • Research Institutes
  • Ambulatory Surgical Centers
  • Tele-radiology Providers
  • Academic Medical Centers
  • Other End Users

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of 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 2023, 2024, 2025, 2026, 2027, 2028, 2030, 3032 and 2034
  • 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
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI Medical Imaging Market, By Modality

  • 5.1 X-ray Imaging
  • 5.2 Computed Tomography (CT)
  • 5.3 Magnetic Resonance Imaging (MRI)
  • 5.4 Ultrasound Imaging
  • 5.5 Nuclear Imaging
  • 5.6 Mammography
  • 5.7 Other Modalities

6 Global AI Medical Imaging Market, By Deployment Mode

  • 6.1 Cloud-based
  • 6.2 On-premise
  • 6.3 Hybrid
  • 6.4 Web-based Platforms
  • 6.5 SaaS Models
  • 6.6 Integrated Systems

7 Global AI Medical Imaging Market, By Technology

  • 7.1 Deep Learning
  • 7.2 Machine Learning
  • 7.3 Natural Language Processing
  • 7.4 Computer Vision
  • 7.5 Cloud-based AI
  • 7.6 Edge AI

8 Global AI Medical Imaging Market, By Application

  • 8.1 Oncology Imaging
  • 8.2 Cardiology Imaging
  • 8.3 Neurology Imaging
  • 8.4 Pulmonology Imaging
  • 8.5 Orthopedic Imaging
  • 8.6 Gastroenterology Imaging
  • 8.7 Other Applications

9 Global AI Medical Imaging Market, By End User

  • 9.1 Hospitals
  • 9.2 Diagnostic Imaging Centers
  • 9.3 Research Institutes
  • 9.4 Ambulatory Surgical Centers
  • 9.5 Tele-radiology Providers
  • 9.6 Academic Medical Centers
  • 9.7 Other End Users

10 Global AI Medical Imaging Market, By Geography

  • 10.1 North America
    • 10.1.1 United States
    • 10.1.2 Canada
    • 10.1.3 Mexico
  • 10.2 Europe
    • 10.2.1 United Kingdom
    • 10.2.2 Germany
    • 10.2.3 France
    • 10.2.4 Italy
    • 10.2.5 Spain
    • 10.2.6 Netherlands
    • 10.2.7 Belgium
    • 10.2.8 Sweden
    • 10.2.9 Switzerland
    • 10.2.10 Poland
    • 10.2.11 Rest of Europe
  • 10.3 Asia Pacific
    • 10.3.1 China
    • 10.3.2 Japan
    • 10.3.3 India
    • 10.3.4 South Korea
    • 10.3.5 Australia
    • 10.3.6 Indonesia
    • 10.3.7 Thailand
    • 10.3.8 Malaysia
    • 10.3.9 Singapore
    • 10.3.10 Vietnam
    • 10.3.11 Rest of Asia Pacific
  • 10.4 South America
    • 10.4.1 Brazil
    • 10.4.2 Argentina
    • 10.4.3 Colombia
    • 10.4.4 Chile
    • 10.4.5 Peru
    • 10.4.6 Rest of South America
  • 10.5 Rest of the World (RoW)
    • 10.5.1 Middle East
      • 10.5.1.1 Saudi Arabia
      • 10.5.1.2 United Arab Emirates
      • 10.5.1.3 Qatar
      • 10.5.1.4 Israel
      • 10.5.1.5 Rest of Middle East
    • 10.5.2 Africa
      • 10.5.2.1 South Africa
      • 10.5.2.2 Egypt
      • 10.5.2.3 Morocco
      • 10.5.2.4 Rest of Africa

11 Strategic Market Intelligence

  • 11.1 Industry Value Network and Supply Chain Assessment
  • 11.2 White-Space and Opportunity Mapping
  • 11.3 Product Evolution and Market Life Cycle Analysis
  • 11.4 Channel, Distributor, and Go-to-Market Assessment

12 Industry Developments and Strategic Initiatives

  • 12.1 Mergers and Acquisitions
  • 12.2 Partnerships, Alliances, and Joint Ventures
  • 12.3 New Product Launches and Certifications
  • 12.4 Capacity Expansion and Investments
  • 12.5 Other Strategic Initiatives

13 Company Profiles

  • 13.1 GE Healthcare
  • 13.2 Siemens Healthineers
  • 13.3 Philips Healthcare
  • 13.4 Canon Medical Systems Corporation
  • 13.5 IBM Watson Health
  • 13.6 Aidoc Medical Ltd.
  • 13.7 Zebra Medical Vision
  • 13.8 Arterys Inc.
  • 13.9 Viz.ai, Inc.
  • 13.10 Enlitic, Inc.
  • 13.11 Qure.ai
  • 13.12 Lunit Inc.
  • 13.13 Butterfly Network, Inc.
  • 13.14 Tempus Labs
  • 13.15 NVIDIA Corporation
  • 13.16 Fujifilm Holdings Corporation
  • 13.17 Samsung Medison
  • 13.18 Agfa-Gevaert Group

List of Tables

  • Table 1 Global AI Medical Imaging Market Outlook, By Region (2023-2034)($MN)
  • Table 2 Global AI Medical Imaging Market Outlook, By Modality (2023-2034)($MN)
  • Table 3 Global AI Medical Imaging Market Outlook, By X-ray Imaging (2023-2034) ($MN)
  • Table 4 Global AI Medical Imaging Market Outlook, By Computed Tomography (CT) (2023-2034)($MN)
  • Table 5 Global AI Medical Imaging Market Outlook, By Magnetic Resonance Imaging (MRI) (2023-2034)($MN)
  • Table 6 Global AI Medical Imaging Market Outlook, By Ultrasound Imaging (2023-2034)($MN)
  • Table 7 Global AI Medical Imaging Market Outlook, By Nuclear Imaging (2023-2034)($MN)
  • Table 8 Global AI Medical Imaging Market Outlook, By Mammography (2023-2034)($MN)
  • Table 9 Global AI Medical Imaging Market Outlook, By Other Modalities (2023-2034)($MN)
  • Table 10 Global AI Medical Imaging Market Outlook, By Deployment Mode (2023-2034) ($MN)
  • Table 11 Global AI Medical Imaging Market Outlook, By Cloud-based (2023-2034)($MN)
  • Table 12 Global AI Medical Imaging Market Outlook, By On-premise (2023-2034) ($MN)
  • Table 13 Global AI Medical Imaging Market Outlook, By Hybrid (2023-2034)($MN)
  • Table 14 Global AI Medical Imaging Market Outlook, By Web-based Platforms (2023-2034)($MN)
  • Table 15 Global AI Medical Imaging Market Outlook, By SaaS Models (2023-2034)($MN)
  • Table 16 Global AI Medical Imaging Market Outlook, By Integrated Systems (2023-2034) ($MN)
  • Table 17 Global AI Medical Imaging Market Outlook, By Technology (2023-2034)($MN)
  • Table 18 Global AI Medical Imaging Market Outlook, By Deep Learning (2023-2034) ($MN)
  • Table 19 Global AI Medical Imaging Market Outlook, By Machine Learning (2023-2034)($MN)
  • Table 20 Global AI Medical Imaging Market Outlook, By Natural Language Processing (2023-2034)($MN)
  • Table 21 Global AI Medical Imaging Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 22 Global AI Medical Imaging Market Outlook, By Cloud-based AI (2023-2034)($MN)
  • Table 23 Global AI Medical Imaging Market Outlook, By Edge AI (2023-2034)($MN)
  • Table 24 Global AI Medical Imaging Market Outlook, By Application (2023-2034)($MN)
  • Table 25 Global AI Medical Imaging Market Outlook, By Oncology Imaging (2023-2034)($MN)
  • Table 26 Global AI Medical Imaging Market Outlook, By Cardiology Imaging (2023-2034)($MN)
  • Table 27 Global AI Medical Imaging Market Outlook, By Neurology Imaging (2023-2034)($MN)
  • Table 28 Global AI Medical Imaging Market Outlook, By Pulmonology Imaging (2023-2034)($MN)
  • Table 29 Global AI Medical Imaging Market Outlook, By Orthopedic Imaging (2023-2034)($MN)
  • Table 30 Global AI Medical Imaging Market Outlook, By Gastroenterology Imaging (2023-2034) ($MN)
  • Table 31 Global AI Medical Imaging Market Outlook, By Other Applications (2023-2034)($MN)
  • Table 32 Global AI Medical Imaging Market Outlook, By End User (2023-2034)($MN)
  • Table 33 Global AI Medical Imaging Market Outlook, By Hospitals (2023-2034)($MN)
  • Table 34 Global AI Medical Imaging Market Outlook, By Diagnostic Imaging Centers (2023-2034)($MN)
  • Table 35 Global AI Medical Imaging Market Outlook, By Research Institutes (2023-2034)($MN)
  • Table 36 Global AI Medical Imaging Market Outlook, By Ambulatory Surgical Centers (2023-2034)($MN)
  • Table 37 Global AI Medical Imaging Market Outlook, By Tele-radiology Providers (2023-2034)($MN)
  • Table 38 Global AI Medical Imaging Market Outlook, By Academic Medical Centers (2023-2034)($MN)
  • Table 39 Global AI Medical Imaging Market Outlook, By Other End Users (2023-2034)($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.