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市場調查報告書
商品編碼
1947475

放射學人工智慧市場：依產品、功能、模式、適應症和最終用戶劃分－全球預測至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個工作天內

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簡介目錄

全球放射學人工智慧市場預計將以21.5%的複合年增長率成長，從2026年的16.9億美元成長到2036年的約118.4億美元。

本報告對全球五大主要地區的放射學人工智慧市場進行了詳細分析，重點關注當前市場趨勢、市場規模、最新發展以及至2036年的預測。透過廣泛的二級和一級研究以及對市場現狀的深入分析，我們對關鍵產業驅動因素、限制因素、機會和挑戰進行了影響分析。

推動放射學人工智慧市場成長的關鍵因素包括：全球對早期疾病檢測的需求不斷增長、醫療機構快速採用自動化診斷成像系統、熟練放射科醫生嚴重短缺以及減少診斷錯誤的必要性。 此外，雲端基礎設施的快速擴張、對高效能演算法、人工智慧驅動的預測分析、多模態人工智慧系統以及醫療保健領域的數位轉型工作的需求不斷增長，預計將為在放射學人工智慧市場運營的公司創造巨大的成長機會。

市場區隔

目錄

第一章：引言

第二章：摘要整理

第三章：市場概覽

  • 市場動態
    • 驅動因素
    • 限制因素
    • 機遇
    • 挑戰
  • 多模態人工智慧與基礎模型對放射學的影響
  • 監管環境（FDA、歐盟人工智慧法、CE認證）
  • 波特五力分析

第四章：全球放射線人工智慧市場依產品/服務劃分

  • 軟體/SaaS
    • 雲端解決方案
    • 混合部署模型
  • 裝置端軟體
    • 嵌入式人工智慧解決方案
    • 邊緣運算平台

第五章：全球放射線人工智慧市場依功能劃分

  • 篩檢和分診
  • 診斷影像與解讀
    • 檢測與分類
    • 量化和測量
  • 治療計畫與介入支持
  • 監測與隨訪
  • 報告和文檔
  • 工作流程優化
  • 研發與臨床開發
  • 其他功能

第六章：全球放射線人工智慧市場依影像方式劃分

  • 電腦斷層攝影(CT)
    • 一般CT
    • 頻譜/光子計數型CT
  • 核磁共振影像(MRI)
  • X光
    • 數位放射線攝影
    • 透視檢驗
  • 超音波
  • 乳房X光攝影
    • 2D乳房X光攝影
    • 斷層攝影
  • 其他的模式(PET，SPECT，核醫學)

第七章 全球放射線人工智慧市場（依適應症劃分）

  • 腫瘤學
    • 肺癌
    • 乳癌
    • 其他癌症
  • 心臟病學
    • 冠狀動脈疾病
    • 結構性心臟病疾病
  • 神經病學
    • 中風與腦血管疾病
    • 創傷性腦損傷
    • 神經退化性疾病
  • 肺科/呼吸系統疾病
    • 肺炎和傳染病
    • 慢性肺部疾病
  • 骨科
    • 骨折檢測
    • 骨齡評估
  • 女性健康
    • 乳房影像
    • 產科影像
  • 其他適應症

第八章 全球放射學人工智慧市場（依最終用戶劃分）

  • 醫院
    • 大學醫院
    • 地區醫院
  • 診斷影像中心
  • 其他的終端用戶(遠隔放射線診斷，研究機關)

第九章 全球放射學人工智慧市場（依地區劃分）

  • 北美
    • 美國
    • 加拿大
  • 歐洲
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙
    • 荷蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 韓國
    • 印度
    • 澳大利亞
    • 其他亞太地區國家
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 其他拉丁美洲國家美洲
  • 中東和非洲

第十章 競爭格局

  • 關鍵成長策略
  • 競爭標竿分析
  • 競爭概覽
    • 行業領導者
    • 市場差異化因素
    • 先鋒企業
    • 新興企業
  • 主要企業市場排名/定位分析（2025 年）

第11章 企業簡介(設備廠商·AI解決方案供應商)

  • 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 附錄

簡介目錄
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