查看購物車
  • Simplified Chinese
  • English
  • Japanese
封面
市場調查報告書
商品編碼
1797972

2032 年診斷影像市場 AI 預測：按組件、模式、部署類型、技術、應用、最終用戶和地區進行全球分析

AI in Diagnostic Imaging Market Forecasts to 2032 - Global Analysis By Component, Modality (X-ray, MRI, CT, Ultrasound, PET, Mammography and Other Modalities), Deployment Mode, Technology, 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個工作天內

價格

根據 Stratistics MRC 的數據，全球診斷成像人工智慧市場預計在 2025 年將達到 16 億美元，到 2032 年將達到 136 億美元，預測期內的複合年成長率為 35.4%。

診斷影像中的人工智慧運用先進的演算法和機器學習模型來分析醫學影像，以提高準確性、效率和臨床決策能力。人工智慧系統有助於偵測異常情況、分割解剖結構，並提升 MRI、CT 和 X 光等多種影像設備的影像品質。透過自動化常規任務並識別細微模式，人工智慧可以幫助放射科醫生更早發現疾病、制定治療方案並最佳化工作流程，最終實現更快的診斷和更個人化的患者照護。

《歐洲放射學》發現，99 家公司開發了 269 個診斷放射學人工智慧應用，主要專注於特定顯像模式或解剖區域內的感知和推理等狹窄任務。

對準確且可擴展的診斷的需求不斷增加

如今，人工智慧演算法能夠以驚人的精確度分析來自核磁共振、CT和X光等設備的大量資料集，從而減少診斷錯誤並加速臨床決策。醫院和診斷影像中心正在採用人工智慧工具來簡化工作流程、提高診療效率並提升診斷準確性。監管核准和報銷框架進一步支持了這一轉變，這些框架檢驗一項臨床資產。

實施和整合成本高

儘管人工智慧具有變革性的潛力，但將其整合到診斷影像系統中，對許多醫療機構而言仍存在財務挑戰。對支援人工智慧的硬體、軟體許可證以及雲端儲存和網路安全等基礎設施升級的前期投資可能令人望而卻步，尤其對於中型和偏遠地區的醫療機構而言。此外，培訓營運和解讀人工智慧輸出所需的人才也增加了營運成本。這些經濟障礙阻礙了人工智慧的普及，尤其是在醫療預算有限、IT生態系統片段化的地區。

將臨床工作流程與多模態人工智慧結合

人工智慧正日益融入端到端診斷工作流程，實現影像系統、電子健康記錄(EHR) 和臨床決策支援工具之間的無縫資料交換。多模態人工智慧的興起，將影像資料與基因組、病理和病史資料結合，為個人化診斷開啟了新的可能性。供應商正在開發支援即時分流、預測分析和縱向病患監測的互通平台。這種融合有望重新定義診斷的準確性，並為人工智慧開發者和醫療保健提供者開闢新的收益來源。

算法偏見和缺乏可解釋性

影像解讀的偏差可能導致誤診和治療延誤，引發倫理和法律問題。此外，許多人工智慧系統如同「黑盒子」般運作，其結論的透明度有限。這種缺乏可解釋性的現象會損害臨床醫生的信任，並使監管核准變得複雜。解決這些問題需要開發強大的檢驗通訊協定、全面的訓練資料集和可解釋的人工智慧框架。

COVID-19的影響：

新冠疫情加速了人工智慧在診斷影像學的應用，尤其是在胸部CT和X光分析領域。人工智慧工具被迅速部署，用於檢測新冠相關異常情況、對患者進行分診以及監測病情進展。然而，供應鏈中斷以及疫情因應資源的重新分配暫時減緩了非新冠影像處理的診療量。疫情過後，對防範準備和數位轉型的關注預計將推動對可擴展的雲端基礎影像處理平台的投資增加，並維持人工智慧的應用。

預計軟體領域將成為預測期內最大的領域

軟體領域預計將在預測期內佔據最大的市場佔有率，這得益於其在實現智慧影像分析方面的核心作用。人工智慧軟體平台整合了深度學習模型、自然語言處理和預測分析，能夠從複雜的影像資料中提供切實可行的洞察。這些平台日益雲端基礎，允許跨多個機構進行可擴展部署。持續的更新和演算法增強確保了其能夠適應不斷變化的臨床需求，使軟體成為人工智慧主導診斷的支柱。

預計 MRI（磁振造影造影）部分將在預測期內實現最高的複合年成長率。

磁振造影(MRI) 領域預計將在預測期內實現最高成長率，這得益於其卓越的軟組織對比度以及在神經病學、腫瘤學和心臟病學領域不斷擴展的應用。人工智慧的整合透過自動化影像分割、提高解析度和縮短掃描時間，增強了 MRI 的效能。超高場強 MRI 和人工智慧輔助功能成像等創新技術正在幫助早期發現阿茲海默症和多發性硬化症等複雜疾病。隨著精準診斷需求的不斷成長，人工智慧 MRI 系統在先進醫療環境中正變得不可或缺。

比最大的地區

在預測期內，北美預計將佔據最大的市場佔有率，得益於其強大的醫療基礎設施、高影像處理和積極的法規結構。該地區受益於強大的研發投入、數位醫療技術的廣泛應用以及針對人工智慧診斷的優惠報銷政策。通用電氣醫療、IBM Watson Health 和西門子醫療等領先公司的總部都設在這裡，推動技術創新和商業化。美國在基於人工智慧的診斷成像工具的臨床試驗和 FDA核准也處於領先地位。

複合年成長率最高的地區：

預計亞太地區將在預測期內實現最高的複合年成長率，這得益於醫療保健支出的不斷成長、診斷服務管道的不斷擴大以及政府推動人工智慧應用的舉措。中國、印度和日本等國家正在大力投資數位醫療基礎設施和人工智慧研究。該地區龐大的患者群體和日益成長的慢性病盛行率為人工智慧主導的影像解決方案創造了肥沃的土壤。本地新興企業和跨國公司正在建立策略夥伴關係，以進入這個快速發展的市場。

免費客製化服務：

此報告的訂閱者可以使用以下免費自訂選項之一：

  • 公司簡介
    • 全面分析其他市場參與者（最多 3 家公司）
    • 主要企業的SWOT分析（最多3家公司）
  • 區域細分
    • 根據客戶興趣對主要國家進行的市場估計、預測和複合年成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 主要研究資料
    • 次級研究資訊來源
    • 先決條件

第3章市場走勢分析

  • 驅動程式
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

5. 全球診斷成像人工智慧市場（按組件）

  • 軟體
    • 基於人工智慧的平台
    • 演算法與解決方案
  • 硬體
    • 整合人工智慧成像設備
    • 伺服器和儲存
    • GPU 和處理器
  • 服務
    • 安裝和整合服務
    • 支援和維護
    • 培訓和諮詢

6. 全球診斷成像人工智慧市場（按模式）

  • X光
  • MRI（磁振造影）
  • CT（電腦斷層掃描）
  • 超音波
  • PET（正子斷層掃描）
  • 乳房X光檢查
  • 其他方式

7. 全球診斷成像人工智慧市場（按實施類型）

  • 雲端基礎
  • 本地

8. 全球診斷成像人工智慧市場（按技術）

  • 深度學習
  • 自然語言處理（NLP）
  • 電腦視覺
  • 生成對抗網路（GAN）
  • 其他技術

9. 全球診斷影像人工智慧市場（按應用）

  • 腫瘤學
  • 心臟病學
  • 神經病學
  • 整形外科
  • 呼吸系統醫療設備
  • 乳房攝影
  • 肝臟和胃腸道成像
  • 口腔診斷
  • 其他應用

第 10 章 診斷影像人工智慧的全球市場（按最終用戶）

  • 醫院
  • 診斷中心
  • 研究辦公室
  • 專科診所
  • 其他最終用戶

第 11 章。按地區分類的全球診斷成像市場 AI

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第12章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第13章：企業概況

  • Arterys
  • Aidoc
  • Zebra Medical Vision
  • Enlitic
  • Qure.ai
  • Infervision
  • Caption Health
  • Lunit
  • Butterfly Network
  • Gauss Surgical
  • Sigtuple
  • Freenome
  • Bay Labs
  • IBM Watson Health Imaging
  • Siemens Healthineers
  • GE Healthcare
  • Philips Healthcare
Product Code: SMRC30342

According to Stratistics MRC, the Global AI in Diagnostic Imaging Market is accounted for $1.6 billion in 2025 and is expected to reach $13.6 billion by 2032 growing at a CAGR of 35.4% during the forecast period. Artificial Intelligence in diagnostic imaging is the use of advanced algorithms and machine learning models to analyze medical images for improved accuracy, efficiency, and clinical decision-making. AI systems assist in detecting abnormalities, segmenting anatomical structures, and enhancing image quality across modalities such as MRI, CT, and X-ray. By automating routine tasks and identifying subtle patterns, AI supports radiologists in early disease detection, treatment planning, and workflow optimization, ultimately contributing to faster diagnoses and more personalized patient care

According to European Radiology identified 269 AI applications in diagnostic radiology, developed by 99 companies. These applications predominantly focus on narrow tasks such as perception and reasoning within specific imaging modalities and anatomical regions.

Market Dynamics:

Driver:

Rising demand for accurate and scalable diagnostics

AI algorithms are now capable of analyzing vast datasets from modalities like MRI, CT, and X-ray with remarkable precision, reducing diagnostic errors and accelerating clinical decision-making. Hospitals and imaging centers are adopting AI tools to streamline workflows, improve throughput, and enhance diagnostic accuracy, especially in high-volume settings. This shift is further supported by regulatory approvals and reimbursement frameworks that validate AI as a clinical asset.

Restraint:

High cost of implementation and integration

Despite its transformative potential, the integration of AI into diagnostic imaging systems remains financially challenging for many healthcare providers. The upfront investment in AI-enabled hardware, software licenses, and infrastructure upgrades such as cloud storage and cybersecurity can be prohibitive, particularly for mid-sized and rural facilities. Moreover, training personnel to operate and interpret AI outputs adds to operational costs. These financial barriers slow down the adoption, especially in regions with limited healthcare budgets or fragmented IT ecosystems.

Opportunity:

Integration with clinical workflows and multimodal AI

AI is increasingly being embedded into end-to-end diagnostic workflows, enabling seamless data exchange between imaging systems, electronic health records (EHRs), and clinical decision support tools. The rise of multimodal AI combining imaging data with genomics, pathology, and patient history is unlocking new possibilities for personalized diagnostics. Vendors are developing interoperable platforms that support real-time triage, predictive analytics, and longitudinal patient monitoring. This convergence is expected to redefine diagnostic precision and open new revenue streams for AI developers and healthcare providers.

Threat:

Algorithmic bias and lack of explainability

Bias in image interpretation can lead to misdiagnosis or delayed treatment, raising ethical and legal concerns. Additionally, many AI systems operate as "black boxes," offering limited transparency into how conclusions are reached. This lack of explainability undermines clinician trust and complicates regulatory approval. Addressing these issues requires robust validation protocols, inclusive training datasets, and the development of interpretable AI frameworks.

Covid-19 Impact:

The COVID-19 pandemic accelerated the adoption of AI in diagnostic imaging, particularly for chest CT and X-ray analysis. AI tools were rapidly deployed to detect COVID-related anomalies, triage patients, and monitor disease progression. However, supply chain disruptions and resource reallocation toward pandemic response temporarily slowed non-COVID imaging volumes. Post-pandemic, the emphasis on preparedness and digital transformation is expected to sustain AI adoption, with increased investment in scalable, cloud-based imaging platforms.

The software segment is expected to be the largest during the forecast period

The software segment is expected to account for the largest market share during the forecast period due to its central role in enabling intelligent image analysis. AI software platforms integrate deep learning models, natural language processing, and predictive analytics to deliver actionable insights from complex imaging data. These platforms are increasingly cloud-based, allowing for scalable deployment across multiple facilities. Continuous updates and algorithm enhancements ensure adaptability to evolving clinical needs, making software the backbone of AI-driven diagnostics.

The MRI (magnetic resonance imaging) segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the MRI (magnetic resonance imaging) segment is predicted to witness the highest growth rate driven by its superior soft tissue contrast and expanding applications in neurology, oncology, and cardiology. AI integration enhances MRI by automating image segmentation, improving resolution, and reducing scan times. Innovations such as ultra-high-field MRI and AI-assisted functional imaging are enabling earlier detection of complex conditions like Alzheimer's and multiple sclerosis. As demand for precision diagnostics grows, AI-powered MRI systems are becoming indispensable in advanced care settings.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share supported by a robust healthcare infrastructure, high imaging volumes, and proactive regulatory frameworks. The region benefits from strong R&D investments, widespread adoption of digital health technologies, and favorable reimbursement policies for AI-enabled diagnostics. Major players like GE HealthCare, IBM Watson Health, and Siemens Healthineers are headquartered here, driving innovation and commercialization. The U.S. also leads in clinical trials and FDA approvals for AI-based imaging tools.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR fueled by rising healthcare expenditure, expanding access to diagnostic services, and government initiatives promoting AI adoption. Countries like China, India, and Japan are investing heavily in digital health infrastructure and AI research. The region's large patient population and increasing prevalence of chronic diseases create a fertile ground for AI-driven imaging solutions. Local startups and global players are forming strategic partnerships to tap into this rapidly evolving market.

Key players in the market

Some of the key players in AI in Diagnostic Imaging Market include Arterys, Aidoc, Zebra Medical Vision, Enlitic, Qure.ai, Infervision, Caption Health, Lunit, Butterfly Network, Gauss Surgical, Sigtuple, Freenome, Bay Labs, IBM Watson Health Imaging, Siemens Healthineers, GE Healthcare, and Philips Healthcare

Key Developments:

In July 2025, AZmed obtained two new FDA clearances for its AI-driven chest X-ray analytics technology, expanding its offerings in diagnostic imaging. These clearances facilitate broader clinical use, enhancing early detection and workflow automation in radiology practices.

In April 2025, Siemens Healthineers showcased its latest diagnostic imaging breakthroughs focused on improving healthcare through advanced AI-powered solutions. The company emphasized enhancing diagnostic productivity, accuracy, and patient outcomes with their cutting-edge imaging technologies during the Asia Oceania Congress of Radiology.

In March 2025, Gleamer acquired Pixyl and Caerus Medical, boosting their proprietary AI imaging portfolio with advanced FDA- and CE-cleared neuro and lumbar MRI AI applications. This expansion positions Gleamer as a leader with comprehensive AI solutions spanning X-ray, mammography, CT, and MRI modalities.

Components Covered:

  • Software
  • Hardware
  • Services

Modalities Covered:

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

Deployment Modes Covered:

  • Cloud-Based
  • On-Premises

Technologies Covered:

  • Deep Learning
  • Natural Language Processing (NLP)
  • Computer Vision
  • Generative Adversarial Networks (GANs)
  • Other Technologies

Applications Covered:

  • Oncology
  • Cardiology
  • Neurology
  • Orthopedics
  • Pulmonology
  • Breast Imaging
  • Liver & GI Imaging
  • Oral Diagnostics
  • Other Applications

End Users Covered:

  • Hospitals
  • Diagnostic Centers
  • Research Laboratories
  • Specialty Clinics
  • 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 alliances

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 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 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 AI in Diagnostic Imaging Market, By Component

  • 5.1 Introduction
  • 5.2 Software
    • 5.2.1 AI-based Platforms
    • 5.2.2 Algorithms & Solutions
  • 5.3 Hardware
    • 5.3.1 Integrated AI-enabled Imaging Devices
    • 5.3.2 Servers & Storage
    • 5.3.3 GPUs & Processors
  • 5.4 Services
    • 5.4.1 Installation & Integration Services
    • 5.4.2 Support & Maintenance
    • 5.4.3 Training & Consulting

6 Global AI in Diagnostic Imaging Market, By Modality

  • 6.1 Introduction
  • 6.2 X-ray
  • 6.3 MRI (Magnetic Resonance Imaging)
  • 6.4 CT (Computed Tomography)
  • 6.5 Ultrasound
  • 6.6 PET (Positron Emission Tomography)
  • 6.7 Mammography
  • 6.8 Other Modalities

7 Global AI in Diagnostic Imaging Market, By Deployment Mode

  • 7.1 Introduction
  • 7.2 Cloud-Based
  • 7.3 On-Premises

8 Global AI in Diagnostic Imaging Market, By Technology

  • 8.1 Introduction
  • 8.2 Deep Learning
  • 8.3 Natural Language Processing (NLP)
  • 8.4 Computer Vision
  • 8.5 Generative Adversarial Networks (GANs)
  • 8.6 Other Technologies

9 Global AI in Diagnostic Imaging Market, By Application

  • 9.1 Introduction
  • 9.2 Oncology
  • 9.3 Cardiology
  • 9.4 Neurology
  • 9.5 Orthopedics
  • 9.6 Pulmonology
  • 9.7 Breast Imaging
  • 9.8 Liver & GI Imaging
  • 9.9 Oral Diagnostics
  • 9.10 Other Applications

10 Global AI in Diagnostic Imaging Market, By End User

  • 10.1 Introduction
  • 10.2 Hospitals
  • 10.3 Diagnostic Centers
  • 10.4 Research Laboratories
  • 10.5 Specialty Clinics
  • 10.6 Other End Users

11 Global AI in Diagnostic Imaging Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 Arterys
  • 13.2 Aidoc
  • 13.3 Zebra Medical Vision
  • 13.4 Enlitic
  • 13.5 Qure.ai
  • 13.6 Infervision
  • 13.7 Caption Health
  • 13.8 Lunit
  • 13.9 Butterfly Network
  • 13.10 Gauss Surgical
  • 13.11 Sigtuple
  • 13.12 Freenome
  • 13.13 Bay Labs
  • 13.14 IBM Watson Health Imaging
  • 13.15 Siemens Healthineers
  • 13.16 GE Healthcare
  • 13.17 Philips Healthcare

List of Tables

  • Table 1 Global AI in Diagnostic Imaging Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI in Diagnostic Imaging Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global AI in Diagnostic Imaging Market Outlook, By Software (2024-2032) ($MN)
  • Table 4 Global AI in Diagnostic Imaging Market Outlook, By AI-based Platforms (2024-2032) ($MN)
  • Table 5 Global AI in Diagnostic Imaging Market Outlook, By Algorithms & Solutions (2024-2032) ($MN)
  • Table 6 Global AI in Diagnostic Imaging Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 7 Global AI in Diagnostic Imaging Market Outlook, By Integrated AI-enabled Imaging Devices (2024-2032) ($MN)
  • Table 8 Global AI in Diagnostic Imaging Market Outlook, By Servers & Storage (2024-2032) ($MN)
  • Table 9 Global AI in Diagnostic Imaging Market Outlook, By GPUs & Processors (2024-2032) ($MN)
  • Table 10 Global AI in Diagnostic Imaging Market Outlook, By Services (2024-2032) ($MN)
  • Table 11 Global AI in Diagnostic Imaging Market Outlook, By Installation & Integration Services (2024-2032) ($MN)
  • Table 12 Global AI in Diagnostic Imaging Market Outlook, By Support & Maintenance (2024-2032) ($MN)
  • Table 13 Global AI in Diagnostic Imaging Market Outlook, By Training & Consulting (2024-2032) ($MN)
  • Table 14 Global AI in Diagnostic Imaging Market Outlook, By Modality (2024-2032) ($MN)
  • Table 15 Global AI in Diagnostic Imaging Market Outlook, By X-ray (2024-2032) ($MN)
  • Table 16 Global AI in Diagnostic Imaging Market Outlook, By MRI (Magnetic Resonance Imaging) (2024-2032) ($MN)
  • Table 17 Global AI in Diagnostic Imaging Market Outlook, By CT (Computed Tomography) (2024-2032) ($MN)
  • Table 18 Global AI in Diagnostic Imaging Market Outlook, By Ultrasound (2024-2032) ($MN)
  • Table 19 Global AI in Diagnostic Imaging Market Outlook, By PET (Positron Emission Tomography) (2024-2032) ($MN)
  • Table 20 Global AI in Diagnostic Imaging Market Outlook, By Mammography (2024-2032) ($MN)
  • Table 21 Global AI in Diagnostic Imaging Market Outlook, By Other Modalities (2024-2032) ($MN)
  • Table 22 Global AI in Diagnostic Imaging Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 23 Global AI in Diagnostic Imaging Market Outlook, By Cloud-Based (2024-2032) ($MN)
  • Table 24 Global AI in Diagnostic Imaging Market Outlook, By On-Premises (2024-2032) ($MN)
  • Table 25 Global AI in Diagnostic Imaging Market Outlook, By Technology (2024-2032) ($MN)
  • Table 26 Global AI in Diagnostic Imaging Market Outlook, By Deep Learning (2024-2032) ($MN)
  • Table 27 Global AI in Diagnostic Imaging Market Outlook, By Natural Language Processing (NLP) (2024-2032) ($MN)
  • Table 28 Global AI in Diagnostic Imaging Market Outlook, By Computer Vision (2024-2032) ($MN)
  • Table 29 Global AI in Diagnostic Imaging Market Outlook, By Generative Adversarial Networks (GANs) (2024-2032) ($MN)
  • Table 30 Global AI in Diagnostic Imaging Market Outlook, By Other Technologies (2024-2032) ($MN)
  • Table 31 Global AI in Diagnostic Imaging Market Outlook, By Application (2024-2032) ($MN)
  • Table 32 Global AI in Diagnostic Imaging Market Outlook, By Oncology (2024-2032) ($MN)
  • Table 33 Global AI in Diagnostic Imaging Market Outlook, By Cardiology (2024-2032) ($MN)
  • Table 34 Global AI in Diagnostic Imaging Market Outlook, By Neurology (2024-2032) ($MN)
  • Table 35 Global AI in Diagnostic Imaging Market Outlook, By Orthopedics (2024-2032) ($MN)
  • Table 36 Global AI in Diagnostic Imaging Market Outlook, By Pulmonology (2024-2032) ($MN)
  • Table 37 Global AI in Diagnostic Imaging Market Outlook, By Breast Imaging (2024-2032) ($MN)
  • Table 38 Global AI in Diagnostic Imaging Market Outlook, By Liver & GI Imaging (2024-2032) ($MN)
  • Table 39 Global AI in Diagnostic Imaging Market Outlook, By Oral Diagnostics (2024-2032) ($MN)
  • Table 40 Global AI in Diagnostic Imaging Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 41 Global AI in Diagnostic Imaging Market Outlook, By End User (2024-2032) ($MN)
  • Table 42 Global AI in Diagnostic Imaging Market Outlook, By Hospitals (2024-2032) ($MN)
  • Table 43 Global AI in Diagnostic Imaging Market Outlook, By Diagnostic Centers (2024-2032) ($MN)
  • Table 44 Global AI in Diagnostic Imaging Market Outlook, By Research Laboratories (2024-2032) ($MN)
  • Table 45 Global AI in Diagnostic Imaging Market Outlook, By Specialty Clinics (2024-2032) ($MN)
  • Table 46 Global AI in Diagnostic Imaging Market Outlook, By Other End Users (2024-2032) ($MN)

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