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市场调查报告书
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1776766

2032 年医疗诊断影像市场人工智慧 (AI) 预测：按显像模式、AI 类型、临床领域、部署模型、组件、应用、最终用户和地区进行全球分析

Artificial Intelligence in Medical Imaging Market Forecasts to 2032 - Global Analysis By Imaging Modality, AI Type, Clinical Area, Deployment Model, Component, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，全球医学影像人工智慧 (AI) 市场规模预计在 2025 年达到 19.7 亿美元，到 2032 年将达到 88.1 亿美元，预测期内的复合年增长率为 23.8%。

医学影像中的人工智慧 (AI) 涉及使用先进的计算模型来评估和解读视觉医疗数据。透过应用机器学习和深度学习技术，AI 可以提高基于影像的诊断的准确性，同时最大限度地减少人为疏忽。它能够自动分析核磁共振成像 (MRI)、 电脑断层扫描和 X 光等影像，从而促进更早的疾病检测和诊断的一致性。这项技术有助于提高影像分辨率，支援预测性洞察，并简化放射学工作流程，帮助临床医生做出更明智的决策。

根据《柳叶刀数位健康》报导，人工智慧系统在31,000多项医疗图像研究中实现了与专业放射科医生相当的诊断准确率，其汇总灵敏度为87%，特异性为92%。同一项Meta分析也发现，人工智慧显着缩短了影像解读时间。

慢性病负担加重，早期诊断需求增加

心血管疾病、癌症和神经系统疾病等慢性疾病的日益流行，推动了对快速精准诊断工具的需求。人工智慧驱动的医学影像诊断能够增强对异常的早期发现，从而实现及时干预并改善治疗效果。医疗保健提供者越来越多地整合人工智慧，以增强放射学评估并简化诊断工作流程。此外，人工智慧快速且准确地分析复杂影像数据的能力对于应对长期照护挑战至关重要。

资料隐私、安全问题和碎片化资料管治

人工智慧系统严重依赖大量医疗资料集，这使得病患隐私问题成为亟待解决的问题。使用云端基础的分析和第三方平台存在未授权存取和资料外洩的风险。此外，不同机构之间管治框架的不一致也使资料共用和标准化工作变得复杂。确保遵守国际资料保护法也增加了复杂性，尤其是在跨司法管辖区部署人工智慧解决方案时。这些问题限制了人工智慧在诊断成像领域的应用速度。

扩展到新的治疗领域和预测分析

人工智慧正从辅助诊断发展到透过预测模型实现主动疾病管理。其功能正在扩展到肿瘤学、心臟病学和神经影像学等领域，有助于更深入地洞察疾病进展。透过识别细微的影像生物标记物，人工智慧可以帮助临床医生预测潜在的健康风险并优化治疗方案。这种不断扩展的应用范围为开发人员和医疗保健组织提供了超越传统影像使用案例的创新机会。

过度依赖人工智慧与放射科医师技能的下降

自动化系统可能导致技能退化，尤其是在常规诊断业务中。此外，由于训练资料有偏差或品质低下，导致人工智慧输出错误，从而导致临床决策失误。缺乏人工监督可能会增加需要细緻判断的复杂病例的风险。向自动化转型需要提升医疗专业人员的技能，使其能够有效地与人工智慧工具合作。在技术支援和人工专业知识之间取得平衡至关重要，以避免损害诊断的准确性和专家能力。

COVID-19的影响：

新冠疫情加速了人工智慧在医学影像领域的整合，尤其是在评估肺部併发症和监测病情进展方面。医院关闭和人满为患凸显了对远距离诊断解决方案和自动化分析的需求。儘管初期资源有限，但疫情刺激了人工智慧主导的影像处理平台的创新。它也加速了临床医生对数位诊断工具进行呼吸评估的接受度。随着医疗保健产业转向数位韧性，影像领域的人工智慧有望成为后疫情时代诊断的基石。

预计预测期内，电脑断层扫描 (CT) 领域将占据最大份额

预计电脑断层扫描 (CT) 领域将在预测期内占据最大市场占有率，因为它能够灵活地捕捉多个专业的高解析度解剖细节。随着人工智慧的融入， 电脑断层扫描的解读变得更快、更准确，从而提高了诊断的可信度。此技术广泛用于检测肿瘤、血管疾病和创伤相关损伤。 CT影像中的人工智慧演算法支援自动分割、异常检测和报告。

定量成像和生物标记部分预计将在预测期内实现最高复合年增长率

预计定量成像和生物标记领域将在预测期内实现最高成长率。这是因为人工智慧工具现在可以从影像数据中提取与疾病严重程度和治疗反应相关的可测量指标。这些生物标记支持个人化病患监测和药物疗效评估。医疗保健机构正在投资整合成像生物标记与基因组和临床数据进行全面分析的平台。

比最大的地区

由于医疗基础设施的不断扩张和技术的快速应用，预计亚太地区将在预测期内占据最大的市场占有率。中国、日本和印度等国的政府正在透过政策支援和官民合作关係推动人工智慧的整合。患者人数的增加和诊断服务可近性的改善正在促进该地区的成长。主导的医学影像诊断正受到广泛欢迎，以解决放射科医生运转率和诊断准确性方面的差距。

复合年增长率最高的地区：

在预测期内，北美预计将实现最高的复合年增长率，这得益于其强大的研发实力、完善的医疗网络和有利的法规。该地区拥有大量专注于开发先进影像处理演算法的人工智慧新兴企业和学术机构。人工智慧在简化临床工作流程和解决放射科医生短缺问题方面的效用已在美国和加拿大广泛认可。人工智慧辅助诊断的监管发展正在推动其商业化，使北美成为全球市场成长的关键驱动力。

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  • 公司简介
    • 对最多三家其他市场公司进行全面分析
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目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 主要研究资料
    • 次级研究资讯来源
    • 先决条件

第三章市场走势分析

  • 驱动程式
  • 抑制因素
  • 机会
  • 威胁
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买家的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5. 全球医学影像人工智慧（AI）在显像模式上的应用

  • X射线
  • 电脑断层扫描（CT）
  • 磁振造影（MRI）
  • 超音波
  • 正子断层扫描（PET）
  • 乳房X光检查
  • 其他成像方式

6. 全球医学影像诊断人工智慧（AI）依类型

  • 机器学习
  • 深度学习
  • 自然语言处理（NLP）
  • 电脑视觉

第七章。按临床领域分類的医学影像诊断中的全球人工智慧（AI）

  • 放射学
  • 心臟病学
  • 神经病学
  • 乳癌筛检/乳房摄影
  • 肿瘤学
  • 呼吸系统和肺
  • 整形外科
  • 其他临床领域

第 8 章：全球医学影像诊断人工智慧 (AI) 部署模式

  • 本地
  • 云端基础
  • 杂交种

9. 全球医学影像人工智慧（AI）组件

  • 软体
    • 人工智慧演算法和模型
    • 人工智慧平台和框架
    • 配备人工智慧的应用程式
  • 硬体
    • 专用处理器
    • 高效能运算 (HPC) 系统
    • 储存解决方案
    • AI融合影像设备
  • 服务
    • 咨询服务
    • 实施和整合服务
    • 资料註释和管理服务

第 10 章。全球人工智慧（AI）在医学影像中的应用

  • 影像分析与解释
  • 电脑辅助诊断（CAD）
  • 定量成像和生物标记
  • 检测和分类
  • 工作流程优化和分类
  • 其他用途

第 11 章。全球医学影像诊断中的人工智慧 (AI)（按最终用户）

  • 医院
  • 诊断影像中心
  • 研究和学术机构
  • 製药和生物技术公司
  • 其他最终用户

第 12 章：全球医学影像人工智慧 (AI) 区域分布

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十三章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第十二章 公司概况

  • Aidoc
  • Arterys
  • Avicenna.AI
  • Canon Medical Systems Corporation
  • CureMetrix
  • Enlitic
  • GE HealthCare
  • HeartFlow Inc.
  • IBM Watson Health
  • Infervision
  • Lunit Inc.
  • Philips Healthcare
  • Qure.ai
  • RadNet
  • Riverain Technologies
  • ScreenPoint Medical
  • Siemens Healthineers
  • Therapixel
  • Zebra Medical Vision
Product Code: SMRC30097

According to Stratistics MRC, the Global Artificial Intelligence (AI) in Medical Imaging Market is accounted for $1.97 billion in 2025 and is expected to reach $8.81 billion by 2032 growing at a CAGR of 23.8% during the forecast period. Artificial Intelligence (AI) in medical imaging involves leveraging advanced computational models to evaluate and interpret visual healthcare data. By applying machine learning and deep learning techniques, AI enhances the precision of image-based diagnostics while minimizing human oversight. It enables automated analysis of modalities like MRI, CT scans, and X-rays, facilitating early disease detection and diagnostic consistency. The technology contributes to improved image resolution, supports predictive insights, and streamlines radiology workflows to assist clinicians in making more informed decisions.

According to The Lancet Digital Health, AI systems achieved diagnostic accuracy comparable to expert radiologists, with pooled sensitivity of 87% and specificity of 92% across over 31,000 medical imaging cases. According to the same meta-analysis, AI also significantly reduced image interpretation time.

Market Dynamics:

Driver:

Rising burden of chronic diseases and demand for early diagnosis

The increasing prevalence of chronic ailments such as cardiovascular conditions, cancer, and neurological disorders has heightened the need for prompt and accurate diagnostic tools. AI-powered medical imaging enhances the detection of anomalies at early stages, allowing for timely intervention and improved treatment outcomes. Healthcare providers are increasingly integrating AI to augment radiological assessments and streamline diagnostic workflows. Moreover AI's ability to analyze complex imaging data swiftly and precisely makes it vital in addressing long-term care challenges.

Restraint:

Data privacy, security concerns, and fragmented data governance

As AI systems rely heavily on vast medical datasets, safeguarding patient privacy has become a pressing issue. The use of cloud-based analytics and third-party platforms introduces risks related to unauthorized access and data breaches. Moreover, inconsistent governance frameworks across institutions complicate data sharing and standardization efforts. Ensuring compliance with international data protection laws adds complexity, especially when deploying AI solutions across different jurisdictions. These concerns collectively restrict the pace of AI adoption in imaging diagnostics.

Opportunity:

Expansion into new therapeutic areas and predictive analytics

AI is evolving from supporting diagnostics to enabling proactive disease management through predictive modeling. Its capabilities are extending to areas such as oncology, cardiology, and neuroimaging, facilitating deeper insights into disease progression. By recognizing subtle imaging biomarkers, AI assists clinicians in forecasting potential health risks and refining treatment plans. This broadening scope presents opportunities for developers and healthcare institutions to innovate beyond traditional imaging use cases.

Threat:

Over-reliance on AI and deskilling of radiologists

Automated systems may cause skill erosion, especially in routine diagnostic tasks. Furthermore, incorrect AI outputs due to biased or poor-quality training data can mislead clinical decisions. A lack of human oversight might increase risks in complex cases requiring nuanced judgment. The shift toward automation necessitates upskilling medical professionals to effectively collaborate with AI tools. Maintaining a balance between technology support and human expertise is essential to avoid undermining diagnostic accuracy and professional competency.

Covid-19 Impact:

The COVID-19 crisis accelerated the integration of AI in medical imaging, especially for assessing lung complications and monitoring disease progression. Lockdowns and hospital overcrowding emphasized the need for remote diagnostic solutions and automated analysis. Despite initial resource constraints, the pandemic catalyzed innovation in AI-driven imaging platforms. It also fostered acceptance among clinicians of digital diagnostic tools for respiratory assessments. As the healthcare sector pivots toward digital resilience, AI in imaging is expected to become a cornerstone of post-pandemic diagnostics.

The computed tomography (CT) segment is expected to be the largest during the forecast period

The computed tomography (CT) segment is expected to account for the largest market share during the forecast period due to its versatility in capturing high-resolution anatomical details across multiple specialties. With the integration of AI, CT scan interpretation has become faster and more accurate, enhancing diagnostic confidence. The modality is widely used for detecting tumors, vascular diseases, and trauma-related injuries. AI algorithms in CT imaging support automated segmentation, anomaly detection, and report generation.

The quantitative imaging & biomarkers segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the quantitative imaging & biomarkers segment is predicted to witness the highest growth rate because AI tools are now capable of extracting measurable indicators from imaging data that correlate with disease severity or response to treatment. These biomarkers support individualized patient monitoring and drug efficacy evaluation. Healthcare institutions are investing in platforms that integrate imaging biomarkers with genomic and clinical data for comprehensive analysis.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share owing to its expanding healthcare infrastructure and rapid technology adoption. Governments across countries like China, Japan, and India are promoting AI integration through policy support and public-private partnerships. Rising patient volumes and improving access to diagnostic services are contributing to regional growth. AI-driven medical imaging is being embraced to address disparities in radiologist availability and diagnostic accuracy.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR fueled by robust R&D, established healthcare networks, and favorable regulations. The region hosts numerous AI startups and academic institutions focused on developing advanced imaging algorithms. AI's utility in streamlining clinical workflows and addressing radiologist shortages is well recognized in the U.S. and Canada. Regulatory progress in AI-enabled diagnostics supports commercialization, positioning North America as a key accelerator of global market growth.

Key players in the market

Some of the key players in Artificial Intelligence (AI) in Medical Imaging Market include Aidoc, Arterys, Avicenna.AI, Canon Medical Systems Corporation, CureMetrix, Enlitic, GE HealthCare, HeartFlow Inc., IBM Watson Health, Infervision, Lunit Inc., Philips Healthcare, Qure.ai, RadNet, Riverain Technologies, ScreenPoint Medical, Siemens Healthineers, Therapixel and Zebra Medical Vision.

Key Developments:

In June 2025, Qure.ai launches AIRA AI-powered co-pilot at the World Health Assembly. The tool aims to reduce manual workload-freeing time for direct patient care responding to the WHO's call for improved health equity.

In May 2025, GE HealthCare unveils enterprise imaging workflow efficiency solutions, introducing a suite of digital tools to optimize imaging operations and support enterprise-level deployments.

In January 2025, Aidoc announces strategic collaboration with AWS to enhance its CARE(TM) Foundation Model using Amazon Web Services' cloud and engineering scale, aiming to deliver real-time clinical AI across multiple imaging modalities.

Imaging Modalities Covered:

  • X-Ray
  • Computed Tomography (CT)
  • Magnetic Resonance Imaging (MRI)
  • Ultrasound
  • Positron Emission Tomography (PET)
  • Mammography
  • Other Imaging Modalities

AI Types Covered:

  • Machine Learning
  • Deep Learning
  • Natural Language Processing (NLP)
  • Computer Vision

Clinical Areas Covered:

  • Radiology
  • Cardiology
  • Neurology
  • Breast Screening/Breast Imaging
  • Oncology
  • Respiratory & Pulmonary
  • Orthopedics
  • Other Clinical Areas

Deployment Models Covered:

  • On-Premise
  • Cloud-based
  • Hybrid

Components Covered:

  • Software
  • Hardware
  • Services

Applications Covered:

  • Image analysis & Interpretation
  • Computer-Aided Diagnosis (CAD)
  • Quantitative Imaging & Biomarkers
  • Detection & Classification
  • Workflow Optimization & Triage
  • Other Applications

End Users Covered:

  • Hospitals
  • Diagnostic Imaging Centers
  • Research Laboratories & Academic Institutions
  • Pharmaceutical & Biotechnology Companies
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • 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 alliance

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Artificial Intelligence (AI) in Medical Imaging Market, By Imaging Modality

  • 5.1 Introduction
  • 5.2 X-Ray
  • 5.3 Computed Tomography (CT)
  • 5.4 Magnetic Resonance Imaging (MRI)
  • 5.5 Ultrasound
  • 5.6 Positron Emission Tomography (PET)
  • 5.7 Mammography
  • 5.8 Other Imaging Modalities

6 Global Artificial Intelligence (AI) in Medical Imaging Market, By AI Type

  • 6.1 Introduction
  • 6.2 Machine Learning
  • 6.3 Deep Learning
  • 6.4 Natural Language Processing (NLP)
  • 6.5 Computer Vision

7 Global Artificial Intelligence (AI) in Medical Imaging Market, By Clinical Area

  • 7.1 Introduction
  • 7.2 Radiology
  • 7.3 Cardiology
  • 7.4 Neurology
  • 7.5 Breast Screening/Breast Imaging
  • 7.6 Oncology
  • 7.7 Respiratory & Pulmonary
  • 7.8 Orthopedics
  • 7.9 Other Clinical Areas

8 Global Artificial Intelligence (AI) in Medical Imaging Market, By Deployment Model

  • 8.1 Introduction
  • 8.2 On-Premise
  • 8.3 Cloud-based
  • 8.4 Hybrid

9 Global Artificial Intelligence (AI) in Medical Imaging Market, By Component

  • 9.1 Introduction
  • 9.2 Software
    • 9.2.1 AI Algorithms & Models
    • 9.2.2 AI Platforms & Frameworks
    • 9.2.3 AI-Powered Applications
  • 9.3 Hardware
    • 9.3.1 Specialized Processors
    • 9.3.2 High-Performance Computing (HPC) Systems
    • 9.3.3 Storage Solutions
    • 9.3.4 AI-Integrated Imaging Devices
  • 9.4 Services
    • 9.4.1 Consulting Services
    • 9.4.2 Implementation & Integration Services
    • 9.4.3 Data Annotation & Curation Services

10 Global Artificial Intelligence (AI) in Medical Imaging Market, By Application

  • 10.1 Introduction
  • 10.2 Image analysis & Interpretation
  • 10.3 Computer-Aided Diagnosis (CAD)
  • 10.4 Quantitative Imaging & Biomarkers
  • 10.5 Detection & Classification
  • 10.6 Workflow Optimization & Triage
  • 10.7 Other Applications

11 Global Artificial Intelligence (AI) in Medical Imaging Market, By End User

  • 11.1 Introduction
  • 11.2 Hospitals
  • 11.3 Diagnostic Imaging Centers
  • 11.4 Research Laboratories & Academic Institutions
  • 11.5 Pharmaceutical & Biotechnology Companies
  • 11.6 Other End Users

12 Global Artificial Intelligence (AI) in Medical Imaging Market, By Geography

  • 12.1 Introduction
  • 12.2 North America
    • 12.2.1 US
    • 12.2.2 Canada
    • 12.2.3 Mexico
  • 12.3 Europe
    • 12.3.1 Germany
    • 12.3.2 UK
    • 12.3.3 Italy
    • 12.3.4 France
    • 12.3.5 Spain
    • 12.3.6 Rest of Europe
  • 12.4 Asia Pacific
    • 12.4.1 Japan
    • 12.4.2 China
    • 12.4.3 India
    • 12.4.4 Australia
    • 12.4.5 New Zealand
    • 12.4.6 South Korea
    • 12.4.7 Rest of Asia Pacific
  • 12.5 South America
    • 12.5.1 Argentina
    • 12.5.2 Brazil
    • 12.5.3 Chile
    • 12.5.4 Rest of South America
  • 12.6 Middle East & Africa
    • 12.6.1 Saudi Arabia
    • 12.6.2 UAE
    • 12.6.3 Qatar
    • 12.6.4 South Africa
    • 12.6.5 Rest of Middle East & Africa

13 Key Developments

  • 13.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 13.2 Acquisitions & Mergers
  • 13.3 New Product Launch
  • 13.4 Expansions
  • 13.5 Other Key Strategies

12 Company Profiling

  • 12.1 Aidoc
  • 12.2 Arterys
  • 12.3 Avicenna.AI
  • 12.4 Canon Medical Systems Corporation
  • 12.5 CureMetrix
  • 12.6 Enlitic
  • 12.7 GE HealthCare
  • 12.8 HeartFlow Inc.
  • 12.9 IBM Watson Health
  • 12.10 Infervision
  • 12.11 Lunit Inc.
  • 12.12 Philips Healthcare
  • 12.13 Qure.ai
  • 12.14 RadNet
  • 12.15 Riverain Technologies
  • 12.16 ScreenPoint Medical
  • 12.17 Siemens Healthineers
  • 12.18 Therapixel
  • 12.19 Zebra Medical Vision

List of Tables

  • Table 1 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Imaging Modality (2024-2032) ($MN)
  • Table 3 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By X-Ray (2024-2032) ($MN)
  • Table 4 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Computed Tomography (CT) (2024-2032) ($MN)
  • Table 5 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Magnetic Resonance Imaging (MRI) (2024-2032) ($MN)
  • Table 6 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Ultrasound (2024-2032) ($MN)
  • Table 7 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Positron Emission Tomography (PET) (2024-2032) ($MN)
  • Table 8 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Mammography (2024-2032) ($MN)
  • Table 9 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Other Imaging Modalities (2024-2032) ($MN)
  • Table 10 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By AI Type (2024-2032) ($MN)
  • Table 11 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Machine Learning (2024-2032) ($MN)
  • Table 12 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Deep Learning (2024-2032) ($MN)
  • Table 13 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Natural Language Processing (NLP) (2024-2032) ($MN)
  • Table 14 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Computer Vision (2024-2032) ($MN)
  • Table 15 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Clinical Area (2024-2032) ($MN)
  • Table 16 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Radiology (2024-2032) ($MN)
  • Table 17 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Cardiology (2024-2032) ($MN)
  • Table 18 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Neurology (2024-2032) ($MN)
  • Table 19 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Breast Screening/Breast Imaging (2024-2032) ($MN)
  • Table 20 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Oncology (2024-2032) ($MN)
  • Table 21 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Respiratory & Pulmonary (2024-2032) ($MN)
  • Table 22 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Orthopedics (2024-2032) ($MN)
  • Table 23 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Other Clinical Areas (2024-2032) ($MN)
  • Table 24 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Deployment Model (2024-2032) ($MN)
  • Table 25 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By On-Premise (2024-2032) ($MN)
  • Table 26 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Cloud-based (2024-2032) ($MN)
  • Table 27 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Hybrid (2024-2032) ($MN)
  • Table 28 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Component (2024-2032) ($MN)
  • Table 29 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Software (2024-2032) ($MN)
  • Table 30 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By AI Algorithms & Models (2024-2032) ($MN)
  • Table 31 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By AI Platforms & Frameworks (2024-2032) ($MN)
  • Table 32 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By AI-Powered Applications (2024-2032) ($MN)
  • Table 33 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 34 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Specialized Processors (2024-2032) ($MN)
  • Table 35 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By High-Performance Computing (HPC) Systems (2024-2032) ($MN)
  • Table 36 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Storage Solutions (2024-2032) ($MN)
  • Table 37 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By AI-Integrated Imaging Devices (2024-2032) ($MN)
  • Table 38 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Services (2024-2032) ($MN)
  • Table 39 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Consulting Services (2024-2032) ($MN)
  • Table 40 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Implementation & Integration Services (2024-2032) ($MN)
  • Table 41 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Data Annotation & Curation Services (2024-2032) ($MN)
  • Table 42 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Application (2024-2032) ($MN)
  • Table 43 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Image analysis & Interpretation (2024-2032) ($MN)
  • Table 44 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Computer-Aided Diagnosis (CAD) (2024-2032) ($MN)
  • Table 45 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Quantitative Imaging & Biomarkers (2024-2032) ($MN)
  • Table 46 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Detection & Classification (2024-2032) ($MN)
  • Table 47 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Workflow Optimization & Triage (2024-2032) ($MN)
  • Table 48 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 49 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By End User (2024-2032) ($MN)
  • Table 50 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Hospitals (2024-2032) ($MN)
  • Table 51 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Diagnostic Imaging Centers (2024-2032) ($MN)
  • Table 52 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Research Laboratories & Academic Institutions (2024-2032) ($MN)
  • Table 53 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Pharmaceutical & Biotechnology Companies (2024-2032) ($MN)
  • Table 54 Global Artificial Intelligence (AI) in Medical Imaging Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.