查看购物车
  • Traditional Chinese
  • English
  • Japanese
  • Korean
封面
市场调查报告书
商品编码
1947475

放射学人工智慧市场：依产品、功能、模式、适应症和最终用户划分－全球预测至2036年

AI for Radiology Market by Offering, Function, Modality, Indication, and End User - Global Forecast to 2036
出版日期: | 出版商: Meticulous Research | 英文 262 Pages | 商品交期: 5-7个工作天内

价格
简介目录

全球放射学人工智慧市场预计将以21.5%的复合年增长率成长，从2026年的16.9亿美元成长到2036年的约118.4亿美元。

本报告对全球五大主要地区的放射学人工智慧市场进行了详细分析，重点关注当前市场趋势、市场规模、最新发展以及至2036年的预测。透过广泛的二级和一级研究以及对市场现状的深入分析，我们对关键产业驱动因素、限制因素、机会和挑战进行了影响分析。

推动放射学人工智慧市场成长的关键因素包括：全球对早期疾病检测的需求不断增长、医疗机构快速采用自动化诊断成像系统、熟练放射科医生严重短缺以及减少诊断错误的必要性。 此外，云端基础设施的快速扩张、对高效能演算法、人工智慧驱动的预测分析、多模态人工智慧系统以及医疗保健领域的数位转型工作的需求不断增长，预计将为在放射学人工智慧市场运营的公司创造巨大的成长机会。

市场区隔

目录

第一章：引言

第二章：摘要整理

第三章：市场概览

  • 市场动态
    • 驱动因素
    • 限制因素
    • 机遇
    • 挑战
  • 多模态人工智慧与基础模型对放射学的影响
  • 监管环境（FDA、欧盟人工智慧法、CE认证）
  • 波特五力分析

第四章：全球放射线人工智慧市场依产品/服务划分

  • 软体/SaaS
    • 云端解决方案
    • 混合部署模型
  • 装置端软体
    • 嵌入式人工智慧解决方案
    • 边缘运算平台

第五章：全球放射线人工智慧市场依功能划分

  • 筛检和分诊
  • 诊断影像与解读
    • 检测与分类
    • 量化和测量
  • 治疗计画与介入支持
  • 监测与随访
  • 报告和文檔
  • 工作流程优化
  • 研发与临床开发
  • 其他功能

第六章：全球放射线人工智慧市场依影像方式划分

  • 电脑断层摄影(CT)
    • 一般CT
    • 频谱/光子计数型CT
  • 核磁共振影像(MRI)
  • X光
    • 数位放射线摄影
    • 透视检验
  • 超音波
  • 乳房X光摄影
    • 2D乳房X光摄影
    • 断层摄影
  • 其他的模式(PET，SPECT，核医学)

第七章 全球放射线人工智慧市场（依适应症划分）

  • 肿瘤学
    • 肺癌
    • 乳癌
    • 其他癌症
  • 心臟病学
    • 冠状动脉疾病
    • 结构性心臟病疾病
  • 神经病学
    • 中风与脑血管疾病
    • 创伤性脑损伤
    • 神经退化性疾病
  • 肺科/呼吸系统疾病
    • 肺炎和传染病
    • 慢性肺部疾病
  • 骨科
    • 骨折检测
    • 骨龄评估
  • 女性健康
    • 乳房影像
    • 产科影像
  • 其他适应症

第八章 全球放射学人工智慧市场（依最终用户划分）

  • 医院
    • 大学医院
    • 地区医院
  • 诊断影像中心
  • 其他的终端用户(远隔放射线诊断，研究机关)

第九章 全球放射学人工智慧市场（依地区划分）

  • 北美
    • 美国
    • 加拿大
  • 欧洲
    • 德国
    • 法国
    • 英国
    • 义大利
    • 西班牙
    • 荷兰
    • 其他欧洲国家
  • 亚太地区
    • 中国
    • 日本
    • 韩国
    • 印度
    • 澳大利亚
    • 其他亚太地区国家
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 其他拉丁美洲国家美洲
  • 中东和非洲

第十章 竞争格局

  • 关键成长策略
  • 竞争标竿分析
  • 竞争概览
    • 行业领导者
    • 市场差异化因素
    • 先锋企业
    • 新兴企业
  • 主要企业市场排名/定位分析（2025 年）

第11章 企业简介(设备厂商·AI解决方案供应商)

  • Siemens Healthineers AG
  • GE HealthCare
  • Koninklijke Philips N.V.
  • Canon Medical Systems Corporation
  • Fujifilm Holdings Corporation
  • Shanghai United Imaging Healthcare Co., Ltd.
  • Hologic, Inc.
  • Aidoc
  • Viz.ai
  • Lunit
  • RapidAI
  • Qure.ai
  • Annalise.ai
  • Rad AI
  • DeepHealth(RadNet, Inc.)
  • Enlitic, Inc.
  • Subtle Medical
  • Cleerly
  • Merative
  • iCAD

第12章 附录

简介目录
Product Code: MRHC - 1041738

AI for Radiology Market by Offering (Software/SaaS, On-Device Software), Function (Screening & Triage, Diagnostic Imaging & Interpretation, Treatment Planning & Intervention Support, Monitoring & Follow-Up, Reporting & Documentation, Workflow Optimization), Modality (Computed Tomography, Magnetic Resonance Imaging, X-Ray, Ultrasound, Mammography), Indication, and End User - Global Forecast to 2036

According to the research report titled, 'AI for Radiology Market by Offering (Software/SaaS, On-Device Software), Function (Screening & Triage, Diagnostic Imaging & Interpretation, Treatment Planning & Intervention Support, Monitoring & Follow-Up, Reporting & Documentation, Workflow Optimization), Modality (Computed Tomography, Magnetic Resonance Imaging, X-Ray, Ultrasound, Mammography), Indication, and End User - Global Forecast to 2036,' the global AI for radiology market is expected to reach approximately USD 11.84 billion by 2036 from USD 1.69 billion in 2026, at a CAGR of 21.5% during the forecast period (2026-2036).

The report provides an in-depth analysis of the global AI for radiology market across five major regions, emphasizing the current market trends, market sizes, recent developments, and forecasts till 2036. Following extensive secondary and primary research and an in-depth analysis of the market scenario, the report conducts the impact analysis of the key industry drivers, restraints, opportunities, and challenges.

The major factors driving the growth of the AI for radiology market include the intensifying global demand for early disease detection, rapid expansion of automated diagnostic imaging systems across healthcare institutions, critical shortage of skilled radiologists, and the need to minimize diagnostic errors. Additionally, the rapid expansion of cloud-based infrastructure, increasing need for high-performance algorithms, AI-powered predictive analytics, multimodal AI systems, and digital transformation initiatives in healthcare are expected to create significant growth opportunities for players operating in the AI for radiology market.

Market Segmentation

The AI for radiology market is segmented by offering (software/SaaS, on-device software), function (screening & triage, diagnostic imaging & interpretation, treatment planning & intervention support, monitoring & follow-up, reporting & documentation, workflow optimization), modality (computed tomography, magnetic resonance imaging, X-ray, ultrasound, mammography), indication (oncology, neurology, cardiology, orthopedics, others), end user (hospitals, diagnostic imaging centers, ambulatory surgery centers), and geography. The study also evaluates industry competitors and analyzes the market at the country level.

Based on Offering

By offering, the software/SaaS segment holds the largest market share in 2026, primarily attributed to its scalable deployment model in supporting rapid implementation and seamless integration within existing healthcare IT environments, such as in large hospital networks and multi-site imaging centers. These systems offer the most comprehensive way to ensure diagnostic consistency across diverse high-volume clinical applications. Software/SaaS solutions are utilized extensively in enterprise healthcare and cloud computing sectors. However, the on-device software segment maintains a significant share due to the growing need for low-latency processing in time-critical diagnostic applications, particularly in emergency departments and stroke centers. The ability to provide instant analysis without cloud connectivity makes on-device software highly attractive for specialized clinical environments.

Based on Function

By function, diagnostic imaging & interpretation segment holds the largest share of the overall market in 2026, driven by the need for comprehensive AI-enabled analysis across diverse imaging modalities. Screening & triage functions represent significant applications for rapid patient prioritization and workflow optimization. Treatment planning & intervention support, monitoring & follow-up, and reporting & documentation represent emerging functions with growing adoption. Workflow optimization functions are expected to witness rapid growth during the forecast period, driven by the growing need for operational efficiency and reduced radiologist burnout. The ability to automate routine tasks and enhance clinical productivity makes workflow optimization highly attractive for healthcare institutions.

Based on Modality

By modality, the computed tomography segment holds the largest share of the overall market in 2026, primarily due to the massive volume of CT procedures performed globally and the rigorous performance standards required for modern diagnostic imaging. Current large-scale healthcare facilities are increasingly specifying AI-enhanced CT solutions to ensure compliance with clinical protocols. Magnetic resonance imaging segment is expected to witness rapid growth during the forecast period, driven by the shift toward integrated diagnostic platforms and the complexity of MRI interpretation workflows. X-ray, ultrasound, and mammography represent significant segments with distinct AI application requirements and clinical workflows.

Based on Indication

By indication, the oncology segment is expected to grow at the fastest CAGR during the forecast period. This rapid expansion stems from the critical need for early cancer detection and the massive global cancer burden requiring advanced diagnostic capabilities. The increasing emphasis on precision oncology and personalized treatment planning is driving demand for AI systems that can identify subtle imaging biomarkers. Neurology segment commands substantial market share in 2026, fueled by expanding applications in stroke detection, traumatic brain injury assessment, and neurodegenerative disease monitoring. Cardiology, orthopedics, and other indications represent specialized segments with distinct diagnostic requirements and clinical applications.

Geographic Analysis

An in-depth geographic analysis of the industry provides detailed qualitative and quantitative insights into the five major regions (North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa) and the coverage of major countries in each region. In 2026, North America dominates the global AI for radiology market with the largest market share, primarily attributed to advanced healthcare infrastructure and the presence of leading technology providers in the U.S. and Canada. The United States alone accounts for a significant portion of global AI radiology adoption, with its position as a hub for healthcare innovation driving sustained growth. Asia-Pacific is expected to witness the fastest growth during the forecast period, supported by rapidly expanding healthcare infrastructure, increasing medical imaging volumes, and government initiatives promoting AI adoption in healthcare. In Europe, the leadership in regulatory frameworks and the push for healthcare digitalization are driving the adoption of AI-powered radiology systems, with countries like Germany, France, and the United Kingdom leading implementations.

Key Players

The key players operating in the global AI for radiology market are Siemens Healthineers AG (Germany), GE HealthCare (U.S.), Koninklijke Philips N.V. (Netherlands), Canon Medical Systems Corporation (Japan), Fujifilm Holdings Corporation (Japan), Shanghai United Imaging Healthcare Co. (China), Hologic, Inc. (U.S.), Merative (U.S.), and emerging AI-native companies such as Aidoc (Israel), Viz.ai (U.S.), Lunit (South Korea), RapidAI (U.S.), Qure.ai (India), Annalise.ai (U.S.), Rad AI (U.S.), DeepHealth (U.S.), Enlitic, Inc. (U.S.), Subtle Medical (U.S.), and Cleerly (U.S.), among others.

Key Questions Answered in the Report

  • What is the current revenue generated by the AI for radiology market globally?
  • At what rate is the global AI for radiology market demand projected to grow for the next 7-10 years?
  • What are the historical market sizes and growth rates of the global AI for radiology market?
  • What are the major factors impacting the growth of this market at the regional and country levels? What are the major opportunities for existing players and new entrants in the market?
  • Which segments in terms of offering, function, modality, and indication are expected to create major traction for the service providers in this market?
  • What are the key geographical trends in this market? Which regions/countries are expected to offer significant growth opportunities for the companies operating in the global AI for radiology market?
  • Who are the major players in the global AI for radiology market? What are their specific service offerings in this market?
  • What are the recent strategic developments in the global AI for radiology market? What are the impacts of these strategic developments on the market?

Scope of the Report:

AI for Radiology Market Assessment -- by Offering

  • Software/SaaS
  • On-Device Software

AI for Radiology Market Assessment -- by Function

  • Screening & Triage
  • Diagnostic Imaging & Interpretation
  • Treatment Planning & Intervention Support
  • Monitoring & Follow-Up
  • Reporting & Documentation
  • Workflow Optimization

AI for Radiology Market Assessment -- by Modality

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

AI for Radiology Market Assessment -- by Indication

  • Oncology
  • Neurology
  • Cardiology
  • Orthopedics
  • Other Indications

AI for Radiology Market Assessment -- by End User

  • Hospitals
  • Diagnostic Imaging Centers
  • Ambulatory Surgery Centers
  • Other End Users

AI for Radiology Market Assessment -- by Geography

  • North America
    • U.S.
    • Canada
  • Europe
    • Germany
    • France
    • UK
    • Italy
    • Spain
    • Rest of Europe
  • Asia-Pacific
    • China
    • India
    • Japan
    • South Korea
    • Southeast Asia
    • Rest of Asia-Pacific
  • Latin America
    • Brazil
    • Mexico
    • Argentina
    • Rest of Latin America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • South Africa
    • Rest of Middle East & Africa

TABLE OF CONTENTS

1. Introduction

  • 1.1. Market Definition
  • 1.2. Market Scope
  • 1.3. Research Methodology
  • 1.4. Assumptions & Limitations

2. Executive Summary

3. Market Overview

  • 3.1. Introduction
  • 3.2. Market Dynamics
    • 3.2.1. Drivers
    • 3.2.2. Restraints
    • 3.2.3. Opportunities
    • 3.2.4. Challenges
  • 3.3. Impact of Multimodal AI and Foundation Models on Radiology
  • 3.4. Regulatory Landscape (FDA, EU AI Act, CE Marking)
  • 3.5. Porter's Five Forces Analysis

4. Global AI for Radiology Market, by Offering

  • 4.1. Introduction
  • 4.2. Software/SaaS
    • 4.2.1. Cloud-Based Solutions
    • 4.2.2. Hybrid Deployment Models
  • 4.3. On-Device Software
    • 4.3.1. Embedded AI Solutions
    • 4.3.2. Edge Computing Platforms

5. Global AI for Radiology Market, by Function

  • 5.1. Introduction
  • 5.2. Screening & Triage
  • 5.3. Diagnostic Imaging & Interpretation
    • 5.3.1. Detection & Classification
    • 5.3.2. Quantification & Measurement
  • 5.4. Treatment Planning & Intervention Support
  • 5.5. Monitoring & Follow-Up
  • 5.6. Reporting & Documentation
  • 5.7. Workflow Optimization
  • 5.8. Research & Clinical Development
  • 5.9. Other Functions

6. Global AI for Radiology Market, by Modality

  • 6.1. Introduction
  • 6.2. Computed Tomography (CT)
    • 6.2.1. General CT
    • 6.2.2. Spectral/Photon-Counting CT
  • 6.3. Magnetic Resonance Imaging (MRI)
  • 6.4. X-Ray
    • 6.4.1. Digital Radiography
    • 6.4.2. Fluoroscopy
  • 6.5. Ultrasound
  • 6.6. Mammography
    • 6.6.1. 2D Mammography
    • 6.6.2. Tomosynthesis
  • 6.7. Other Modalities (PET, SPECT, Nuclear Medicine)

7. Global AI for Radiology Market, by Indication

  • 7.1. Introduction
  • 7.2. Oncology
    • 7.2.1. Lung Cancer
    • 7.2.2. Breast Cancer
    • 7.2.3. Other Cancers
  • 7.3. Cardiology
    • 7.3.1. Coronary Artery Disease
    • 7.3.2. Structural Heart Disease
  • 7.4. Neurology
    • 7.4.1. Stroke & Cerebrovascular Disease
    • 7.4.2. Traumatic Brain Injury
    • 7.4.3. Neurodegenerative Diseases
  • 7.5. Pulmonology/Respiratory Diseases
    • 7.5.1. Pneumonia & Infections
    • 7.5.2. Chronic Lung Diseases
  • 7.6. Orthopedics
    • 7.6.1. Fracture Detection
    • 7.6.2. Bone Age Assessment
  • 7.7. Women's Health
    • 7.7.1. Breast Imaging
    • 7.7.2. Obstetric Imaging
  • 7.8. Other Indications

8. Global AI for Radiology Market, by End User

  • 8.1. Introduction
  • 8.2. Hospitals
    • 8.2.1. Academic Medical Centers
    • 8.2.2. Community Hospitals
  • 8.3. Diagnostic Imaging Centers
  • 8.4. Other End Users (Teleradiology, Research Institutions)

9. Global AI for Radiology Market, by Region

  • 9.1. Introduction
  • 9.2. North America
    • 9.2.1. U.S.
    • 9.2.2. Canada
  • 9.3. Europe
    • 9.3.1. Germany
    • 9.3.2. France
    • 9.3.3. U.K.
    • 9.3.4. Italy
    • 9.3.5. Spain
    • 9.3.6. Netherlands
    • 9.3.7. Rest of Europe
  • 9.4. Asia-Pacific
    • 9.4.1. China
    • 9.4.2. Japan
    • 9.4.3. South Korea
    • 9.4.4. India
    • 9.4.5. Australia
    • 9.4.6. Rest of Asia-Pacific
  • 9.5. Latin America
    • 9.5.1. Brazil
    • 9.5.2. Mexico
    • 9.5.3. Rest of Latin America
  • 9.6. Middle East & Africa

10. Competitive Landscape

  • 10.1. Overview
  • 10.2. Key Growth Strategies
  • 10.3. Competitive Benchmarking
  • 10.4. Competitive Dashboard
    • 10.4.1. Industry Leaders
    • 10.4.2. Market Differentiators
    • 10.4.3. Vanguards
    • 10.4.4. Emerging Companies
  • 10.5. Market Ranking/Positioning Analysis of Key Players, 2025

11. Company Profiles (Equipment Manufacturers & AI Solution Providers)

  • 11.1. Siemens Healthineers AG
  • 11.2. GE HealthCare
  • 11.3. Koninklijke Philips N.V.
  • 11.4. Canon Medical Systems Corporation
  • 11.5. Fujifilm Holdings Corporation
  • 11.6. Shanghai United Imaging Healthcare Co., Ltd.
  • 11.7. Hologic, Inc.
  • 11.8. Aidoc
  • 11.9. Viz.ai
  • 11.10. Lunit
  • 11.11. RapidAI
  • 11.12. Qure.ai
  • 11.13. Annalise.ai
  • 11.14. Rad AI
  • 11.15. DeepHealth (RadNet, Inc.)
  • 11.16. Enlitic, Inc.
  • 11.17. Subtle Medical
  • 11.18. Cleerly
  • 11.19. Merative
  • 11.20. iCAD

12. Appendix

  • 12.1. Questionnaire
  • 12.2. Related Reports