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市场调查报告书
商品编码
1797972

2032 年诊断影像市场 AI 预测：按组件、模式、部署类型、技术、应用、最终用户和地区进行全球分析

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个工作天内

价格

根据 Stratistics MRC 的数据，全球诊断成像人工智慧市场预计在 2025 年将达到 16 亿美元，到 2032 年将达到 136 亿美元，预测期内的复合年增长率为 35.4%。

诊断影像中的人工智慧运用先进的演算法和机器学习模型来分析医学影像，以提高准确性、效率和临床决策能力。人工智慧系统有助于侦测异常情况、分割解剖结构，并提升 MRI、CT 和 X 光等多种影像设备的影像品质。透过自动化常规任务并识别细微模式，人工智慧可以帮助放射科医生更早发现疾病、制定治疗方案并优化工作流程，最终实现更快的诊断和更个人化的患者照护。

《欧洲放射学》发现，99 家公司开发了 269 个诊断放射学人工智慧应用，主要专注于特定显像模式或解剖区域内的感知和推理等狭窄任务。

对准确且可扩展的诊断的需求不断增加

如今，人工智慧演算法能够以惊人的精确度分析来自核磁共振、CT和X光等设备的大量资料集，从而减少诊断错误并加速临床决策。医院和诊断影像中心正在采用人工智慧工具来简化工作流程、提高诊疗效率并提升诊断准确性。监管核准和报销框架进一步支持了这一转变，这些框架检验一项临床资产。

实施和整合成本高

儘管人工智慧具有变革性的潜力，但将其整合到诊断影像系统中，对许多医疗机构而言仍存在财务挑战。对支援人工智慧的硬体、软体许可证以及云端储存和网路安全等基础设施升级的前期投资可能令人望而却步，尤其对于中型和偏远地区的医疗机构而言。此外，培训营运和解读人工智慧输出所需的人才也增加了营运成本。这些经济障碍阻碍了人工智慧的普及，尤其是在医疗预算有限、IT生态系统片段化的地区。

将临床工作流程与多模态人工智慧结合

人工智慧正日益融入端到端诊断工作流程，实现影像系统、电子健康记录(EHR) 和临床决策支援工具之间的无缝资料交换。多模态人工智慧的兴起，将影像资料与基因组、病理和病史资料结合，为个人化诊断开启了新的可能性。供应商正在开发支援即时分流、预测分析和纵向病患监测的互通平台。这种融合有望重新定义诊断的准确性，并为人工智慧开发者和医疗保健提供者开闢新的收益来源。

算法偏见和缺乏可解释性

影像解读的偏差可能导致误诊和治疗延误，引发伦理和法律问题。此外，许多人工智慧系统如同「黑盒子」般运作，其结论的透明度有限。这种缺乏可解释性的现象会损害临床医生的信任，并使监管核准变得复杂。解决这些问题需要开发强大的检验通讯协定、全面的训练资料集和可解释的人工智慧框架。

COVID-19的影响：

新冠疫情加速了人工智慧在诊断影像学的应用，尤其是在胸部CT和X光分析领域。人工智慧工具被迅速部署，用于检测新冠相关异常情况、对患者进行分诊以及监测病情进展。然而，供应链中断以及疫情因应资源的重新分配暂时减缓了非新冠影像处理的诊疗量。疫情过后，对防范准备和数位转型的关注预计将推动对可扩展的云端基础影像处理平台的投资增加，并维持人工智慧的应用。

预计软体领域将成为预测期内最大的领域

软体领域预计将在预测期内占据最大的市场占有率，这得益于其在实现智慧影像分析方面的核心作用。人工智慧软体平台整合了深度学习模型、自然语言处理和预测分析，能够从复杂的影像资料中提供切实可行的洞察。这些平台日益云端基础，允许跨多个机构进行可扩展部署。持续的更新和演算法增强确保了其能够适应不断变化的临床需求，使软体成为人工智慧主导诊断的支柱。

预计 MRI（磁振造影造影）部分将在预测期内实现最高的复合年增长率。

磁振造影(MRI) 领域预计将在预测期内实现最高成长率，这得益于其卓越的软组织对比度以及在神经病学、肿瘤学和心臟病学领域不断扩展的应用。人工智慧的整合透过自动化影像分割、提高解析度和缩短扫描时间，增强了 MRI 的效能。超高场强 MRI 和人工智慧辅助功能成像等创新技术正在帮助早期发现阿兹海默症和多发性硬化症等复杂疾病。随着精准诊断需求的不断增长，人工智慧 MRI 系统在先进医疗环境中正变得不可或缺。

比最大的地区

在预测期内，北美预计将占据最大的市场占有率，得益于其强大的医疗基础设施、高影像处理和积极的法规结构。该地区受益于强大的研发投入、数位医疗技术的广泛应用以及针对人工智慧诊断的优惠报销政策。通用电气医疗、IBM Watson Health 和西门子医疗等领先公司的总部都设在这里，推动技术创新和商业化。美国在基于人工智慧的诊断成像工具的临床试验和 FDA核准也处于领先地位。

复合年增长率最高的地区：

预计亚太地区将在预测期内实现最高的复合年增长率，这得益于医疗保健支出的不断增长、诊断服务管道的不断扩大以及政府推动人工智慧应用的倡议。中国、印度和日本等国家正在大力投资数位医疗基础设施和人工智慧研究。该地区庞大的患者群体和日益增长的慢性病盛行率为人工智慧主导的影像解决方案创造了肥沃的土壤。本地新兴企业和跨国公司正在建立策略伙伴关係，以进入这个快速发展的市场。

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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
  • 技术分析
  • 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
  • 买方的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5. 全球诊断成像人工智慧市场（按组件）

  • 软体
    • 基于人工智慧的平台
    • 演算法与解决方案
  • 硬体
    • 整合人工智慧成像设备
    • 伺服器和储存
    • GPU 和处理器
  • 服务
    • 安装和整合服务
    • 支援和维护
    • 培训和咨询

6. 全球诊断成像人工智慧市场（按模式）

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

7. 全球诊断成像人工智慧市场（按实施类型）

  • 云端基础
  • 本地

8. 全球诊断成像人工智慧市场（按技术）

  • 深度学习
  • 自然语言处理（NLP）
  • 电脑视觉
  • 生成对抗网路（GAN）
  • 其他技术

9. 全球诊断影像人工智慧市场（按应用）

  • 肿瘤学
  • 心臟病学
  • 神经病学
  • 整形外科
  • 呼吸系统医疗设备
  • 乳房摄影
  • 肝臟和胃肠道成像
  • 口腔诊断
  • 其他应用

第 10 章 诊断影像人工智慧的全球市场（按最终用户）

  • 医院
  • 诊断中心
  • 研究办公室
  • 专科诊所
  • 其他最终用户

第 11 章。按地区分類的全球诊断成像市场 AI

  • 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
    • 其他南美
  • 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

第十二章 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

第十三章：企业概况

  • 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.