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市場調查報告書
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2046099

人工智慧在醫學影像領域的市場－全球產業規模、佔有率、趨勢、機會和預測：按技術、應用、模式、最終用途、地區和競爭格局分類，2021-2031年

AI In Medical Imaging Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Technology, By Application, By Modalities, By End Use, By Region & Competition, 2021-2031F
出版日期: | 出版商: TechSci Research | 英文 180 Pages | 商品交期: 2-3個工作天內

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簡介目錄

全球醫學影像領域人工智慧市場預計將從 2025 年的 16.5 億美元大幅成長至 2031 年的 43.5 億美元，複合年成長率達 17.54%。

在這一領域，機器學習和深度學習演算法被用於分析各種診斷影像，例如X光片、 電腦斷層掃描和MRI影像，旨在識別疾病並量化生理資訊。影像資料量的不斷成長是推動市場成長的主要因素。這需要自動化解決方案來減輕放射科醫生的工作量並提高處理速度。此外，對早期疾病檢測的需求以及向基於價值的醫療保健模式的轉變，也進一步推動了這些技術的應用，以提高診斷準確性和營運效率。

市場概覽
預測期 2027-2031
市場規模：2025年 16.5億美元
市場規模：2031年 43.5億美元
複合年成長率：2026-2031年 17.54%
成長最快的細分市場 神經病學
最大的市場 北美洲

然而，將這些人工智慧工具順利整合到現有的臨床工作流程和電子健康記錄（EHR）系統中面臨許多挑戰，阻礙了市場發展。因此，解決方案往往各自獨立，互通性差，導致應用推廣延遲。監管趨勢也推動了該領域的快速發展。根據美國放射學會（ACR）統計，2024年FDA核准的醫療人工智慧演算法中，約80%用於放射學應用。如此高的核准率凸顯了該領域的快速發展，同時也凸顯了在各種臨床環境中檢驗和有效部署這些眾多模型的巨大挑戰。

市場促進因素

推動醫學影像領域採用人工智慧的主要動力之一是放射科醫生和合格影像專家的嚴重短缺。需要解讀的醫學影像數量不斷增加，加上可用人員缺口日益擴大，迫使醫療機構採用自動化人工智慧解決方案。這些解決方案有助於優先處理高優先病例並減輕行政負擔。這種短缺的嚴重程度在英國等國家尤其明顯。根據英國皇家放射學院於2024年6月發布的《2023年臨床放射學普查報告》，如果目前的招募和留任趨勢持續下去，預計到2028年，臨床放射科醫師的缺口將達到30%。這使得人工智慧不僅能夠提升臨床功能，而且成為醫院必不可少的營運要素，對於維持醫療服務的連續性和管理待處理病例至關重要。

同時，來自創業投資和政府的資金大幅增加，正在加速人工智慧演算法從概念階段向市場化產品的開發。這些資金支持使開發人員能夠完善深度學習模型並應對複雜的監管流程，從而更快地將可靠的工具推向市場。例如，Rad AI 在 2024 年 5 月宣布的 B 輪資金籌措中，獲得了 5,000 萬美元的投資，用於推動生成式人工智慧技術的發展，以實現放射診斷報告的自動化，這充分展現了這一資金籌措的強勁勢頭。此類投資直接促進了人工智慧產品供應的擴大，美國食品藥物管理局(FDA) 也強調了這個趨勢。 FDA 報告稱，截至 2024 年，已有超過 950 種人工智慧和機器學習醫療設備核准，這清楚地表明了資本對市場供應的影響。

市場挑戰

全球醫學影像人工智慧市場面臨的一大障礙是難以將人工智慧工具整合到現有的臨床工作流程和電子健康記錄系統中。儘管這些演算法在診斷方面具有優勢，但它們通常作為獨立系統運行，缺乏與影像歸檔和通訊系統（PACS）的有效整合。這種碎片化迫使放射科醫生在各種應用程式之間切換才能獲取人工智慧產生的信息，導致管理效率低下，抵消了自動化可能帶來的時間節省優勢。因此，臨床醫生面臨更大的認知負擔，並且往往不願意採用會擾亂既有診斷流程的解決方案。

互通性的缺失直接阻礙了市場成長，延緩了醫療機構的廣泛應用。醫療服務提供者不願投資那些需要複雜定製配置或結果無法無縫整合到患者病歷中的技術，從而延長了應用時間。歐洲放射學會 (ESR) 2024 年的報告顯示，24% 的放射科專業人員認為 IT 和系統整合是人工智慧在臨床實踐中應用的主要障礙。如果沒有簡單易用的「即插即用」相容性，人工智慧創新將難以超越最初的試點階段，發展成為擴充性的、能夠產生收入的業務，從而限制整個產業的成長潛力。

市場趨勢

隨著生成式人工智慧在合成資料生成和影像重建領域的應用，市場正經歷重大變革。這項技術有效應對了數據稀缺等挑戰，並提升了掃描品質。與依賴海量標註資料集的傳統診斷演算法不同，生成式模型現在用於產生高解析度合成影像進行訓練。這不僅緩解了隱私擔憂，也減少了資料集中的偏差。此外，這項技術正在革新影像重建方式，能夠利用低劑量輸入資料來產生診斷等級的掃描影像。這顯著降低了患者的輻射暴露量，並加快了磁振造影掃描速度。這種向生成式人工智慧的策略性轉變，在其在整個產業的快速普及中得到了清晰的體現。根據英偉達2025年3月發布的報告《醫療保健和生命科學領域的人工智慧現狀：2025年趨勢》，54%的醫療機構正在積極使用生成式人工智慧工作負載，這表明醫療機構正在從純粹的分析模型轉向創新的數據解決方案。

同時，人工智慧驅動的工作流程自動化和分診解決方案的擴展正成為緩解放射科工作負擔的關鍵方案。這些系統如今在管理整個放射科流程中發揮著越來越重要的作用，從自動選擇診療方案到智慧地對工作列表中的危重病例進行優先排序，而不僅僅關注診斷敏感性。這一趨勢強調減輕行政任務帶來的認知負擔和職業倦怠，並確保能夠立即突出顯示緊急病灶以吸引放射科醫生的注意力，而不僅僅是關注診斷敏感性。 2025年1月發表於《美國放射學會雜誌》的《放射學中的人工智慧：領導力調查》研究報告也印證了這項營運需求的廣泛認可。在該調查中，100%受訪的大學放射科主任表示計劃實施人工智慧，尤其希望藉此提高科室品質和營運效率。

目錄

第1章概述

第2章：調查方法

第3章執行摘要

第4章：客戶心聲

第5章：全球人工智慧醫療影像診斷市場展望

  • 市場規模及預測
    • 按金額
  • 市佔率及預測
    • 透過科技（深度學習、自然語言處理等）
    • 按應用領域（神經科、呼吸/肺科、心臟科、乳癌篩檢、整形外科、其他）
    • 按檢查方式（電腦斷層掃描、MRI、X光、超音波、核子醫學）
    • 依最終用途（醫院、診斷影像中心、其他）
    • 按地區
    • 按公司（2025 年）
  • 市場地圖

第6章：北美醫療影像人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 北美洲：國別分析
    • 美國
    • 加拿大
    • 墨西哥

第7章：歐洲醫學影像人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 歐洲：國別分析
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙

第8章：亞太地區醫療影像人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 亞太地區：國別分析
    • 中國
    • 印度
    • 日本
    • 韓國
    • 澳洲

第9章：中東和非洲醫療影像診斷人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 中東與非洲：國別分析
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 南非

第10章：南美洲醫學影像人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 南美洲：國別分析
    • 巴西
    • 哥倫比亞
    • 阿根廷

第11章 市場動態

  • 促進因素
  • 任務

第12章 市場趨勢與發展

  • 併購
  • 產品發布
  • 近期趨勢

第13章：全球人工智慧在醫學影像領域的市場：SWOT分析

第14章：波特五力分析

  • 產業競爭
  • 新進入者的潛力
  • 供應商的議價能力
  • 顧客權力
  • 替代品的威脅

第15章 競爭格局

  • Digital Diagnostics Inc.
  • Tempus AI, Inc.
  • Advanced Micro Devices, Inc.
  • HeartFlow, Inc.
  • Enlitic, Inc.
  • Viz.ai, Inc.
  • EchoNous Inc.
  • HeartVista Inc.
  • Exo Imaging, Inc.
  • Nano-X Imaging Ltd.

第16章 策略建議

第17章：關於研究公司及免責聲明

簡介目錄
Product Code: 27541

The global market for AI in medical imaging is projected to expand significantly, rising from USD 1.65 billion in 2025 to USD 4.35 billion by 2031, demonstrating a compound annual growth rate (CAGR) of 17.54%. This sector utilizes machine learning and deep learning algorithms to analyze various diagnostic images, including X-rays, CT scans, and MRIs, with the aim of identifying diseases and quantifying physiological information. Key factors propelling this market growth include the increasing volume of imaging data, which necessitates automated solutions to alleviate radiologist burnout and enhance processing speed. Additionally, the demand for early disease detection and a shift towards value-based healthcare models are further encouraging the adoption of these technologies to boost diagnostic accuracy and operational efficiency.

Market Overview
Forecast Period2027-2031
Market Size 2025USD 1.65 Billion
Market Size 2031USD 4.35 Billion
CAGR 2026-203117.54%
Fastest Growing SegmentNeurology
Largest MarketNorth America

However, the market's progress is hindered by challenges in smoothly integrating these AI tools into existing clinical workflows and electronic health record (EHR) systems, often resulting in isolated, non-interoperable solutions that slow down implementation. The rapid advancement in this field is underscored by regulatory trends; in 2024, approximately 80% of all medical AI algorithms cleared by the FDA were radiology applications, as reported by the American College of Radiology. While this high rate of clearance highlights the sector's swift development, it also emphasizes the substantial challenge of validating and effectively deploying these numerous models across diverse clinical settings.

Market Driver

A major driving force behind the adoption of artificial intelligence in diagnostic imaging is the severe shortage of radiologists and qualified imaging specialists. The growing gap between the increasing volume of medical images requiring interpretation and the limited available workforce is compelling healthcare providers to implement automated AI solutions. These solutions help prioritize urgent cases and reduce administrative workloads. The severity of this staffing issue is evident in systems like the United Kingdom, where the Royal College of Radiologists' June 2024 'Clinical Radiology Census 2023' projects a 30% deficit in clinical radiologists by 2028 if current recruitment and retention patterns continue. This makes AI an operational imperative for hospitals, crucial for maintaining care continuity and managing backlogs, rather than just a clinical enhancement.

Simultaneously, a significant rise in venture capital and government funding is accelerating the development of AI algorithms from conceptual stages to market-ready products. This financial backing enables developers to refine their deep learning models and navigate intricate regulatory processes, thereby expediting the market introduction of reliable tools. For instance, Rad AI's May 2024 'Series B Funding Announcement' revealed a $50 million investment to advance its generative AI for automating radiology reporting, illustrating this financial momentum. Such investments directly contribute to a greater availability of AI products, a trend highlighted by the U.S. Food and Drug Administration, which reported over 950 authorized AI and machine learning-enabled medical devices by 2024, showcasing the clear impact of capital on market supply.

Market Challenge

A significant obstacle for the global AI in medical imaging market is the difficulty of integrating AI tools into existing clinical workflows and electronic health record systems. While these algorithms offer diagnostic benefits, they frequently operate as isolated systems, lacking effective communication with Picture Archiving and Communication Systems (PACS). This fragmentation forces radiologists to switch between various applications to access AI-generated insights, introducing administrative inefficiencies that counteract the potential time savings from automation. As a result, clinicians experience increased cognitive burden and are often reluctant to adopt solutions that disrupt their established diagnostic processes.

This lack of interoperability directly hinders market growth by delaying widespread deployment across healthcare facilities. Providers are hesitant to invest in technologies that demand complex, customized setups or fail to seamlessly integrate results into patient records, which prolongs procurement timelines. A 2024 report by the European Society of Radiology indicated that 24% of radiology professionals consider IT and systems integration as a primary barrier to AI implementation in clinical practice. Without straightforward, "plug-and-play" compatibility, AI innovations struggle to move beyond initial pilot phases to become scalable, revenue-generating operations, thereby restricting the sector's overall growth potential.

Market Trends

The market is undergoing a significant transformation with the adoption of generative AI for synthetic data generation and image reconstruction, addressing issues like data scarcity and improving scan quality. Unlike conventional diagnostic algorithms that depend on extensive labeled datasets, generative models are now used to produce high-fidelity synthetic images for training, which helps to alleviate privacy concerns and reduce dataset bias. Moreover, this technology is transforming image reconstruction, allowing for the creation of diagnostic-grade scans from lower-dose inputs, thereby substantially decreasing patient radiation exposure and speeding up MRI acquisition. This strategic pivot towards generative AI is clearly reflected in its swift industry adoption; a March 2025 NVIDIA report, 'State of AI in Healthcare and Life Sciences: 2025 Trends', stated that 54% of healthcare organizations are actively utilizing generative AI workloads, signaling a move beyond purely analytical models towards innovative data solutions.

Concurrently, the expansion of AI-driven workflow automation and triage solutions is emerging as a vital response to the operational overload faced by radiology departments. These systems are now taking on broader roles beyond just pixel-level diagnosis, increasingly managing the entire radiology process, from automated protocol selection to intelligently prioritizing critical cases in worklists. This trend emphasizes reducing cognitive burden and administrative burnout, ensuring that urgent pathologies are immediately highlighted for radiologist attention, rather than solely focusing on diagnostic sensitivity. The widespread acknowledgment of this operational necessity is underscored by a January 2025 study in the Journal of the American College of Radiology, 'Artificial Intelligence in Radiology: A Leadership Survey', where 100% of academic radiology chairs surveyed indicated plans to implement AI specifically to enhance departmental quality and operational efficiency.

Key Market Players

  • Digital Diagnostics Inc.
  • Tempus AI, Inc.
  • Advanced Micro Devices, Inc.
  • HeartFlow, Inc.
  • Enlitic, Inc.
  • Viz.ai, Inc.
  • EchoNous Inc.
  • HeartVista Inc.
  • Exo Imaging, Inc.
  • Nano-X Imaging Ltd.

Report Scope

In this report, the Global AI In Medical Imaging Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

AI In Medical Imaging Market, By Technology

  • Deep Learning
  • Natural Language Processing
  • Others

AI In Medical Imaging Market, By Application

  • Neurology
  • Respiratory & Pulmonary
  • Cardiology
  • Breast Screening
  • Orthopedics
  • Others

AI In Medical Imaging Market, By Modalities

  • CT scan
  • MRI
  • X-rays
  • Ultrasound
  • Nuclear Imaging

AI In Medical Imaging Market, By End Use

  • Hospitals
  • Diagnostic Imaging Centers
  • Others

AI In Medical Imaging Market, By Region

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • France
    • United Kingdom
    • Italy
    • Germany
    • Spain
  • Asia Pacific
    • China
    • India
    • Japan
    • Australia
    • South Korea
  • South America
    • Brazil
    • Argentina
    • Colombia
  • Middle East & Africa
    • South Africa
    • Saudi Arabia
    • UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global AI In Medical Imaging Market.

Available Customizations:

Global AI In Medical Imaging Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Key Industry Partners
  • 2.4. Major Association and Secondary Sources
  • 2.5. Forecasting Methodology
  • 2.6. Data Triangulation & Validation
  • 2.7. Assumptions and Limitations

3. Executive Summary

  • 3.1. Overview of the Market
  • 3.2. Overview of Key Market Segmentations
  • 3.3. Overview of Key Market Players
  • 3.4. Overview of Key Regions/Countries
  • 3.5. Overview of Market Drivers, Challenges, Trends

4. Voice of Customer

5. Global AI In Medical Imaging Market Outlook

  • 5.1. Market Size & Forecast
    • 5.1.1. By Value
  • 5.2. Market Share & Forecast
    • 5.2.1. By Technology (Deep Learning, Natural Language Processing, Others)
    • 5.2.2. By Application (Neurology, Respiratory & Pulmonary, Cardiology, Breast Screening, Orthopedics, Others)
    • 5.2.3. By Modalities (CT scan, MRI, X-rays, Ultrasound, Nuclear Imaging)
    • 5.2.4. By End Use (Hospitals, Diagnostic Imaging Centers, Others)
    • 5.2.5. By Region
    • 5.2.6. By Company (2025)
  • 5.3. Market Map

6. North America AI In Medical Imaging Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Technology
    • 6.2.2. By Application
    • 6.2.3. By Modalities
    • 6.2.4. By End Use
    • 6.2.5. By Country
  • 6.3. North America: Country Analysis
    • 6.3.1. United States AI In Medical Imaging Market Outlook
      • 6.3.1.1. Market Size & Forecast
        • 6.3.1.1.1. By Value
      • 6.3.1.2. Market Share & Forecast
        • 6.3.1.2.1. By Technology
        • 6.3.1.2.2. By Application
        • 6.3.1.2.3. By Modalities
        • 6.3.1.2.4. By End Use
    • 6.3.2. Canada AI In Medical Imaging Market Outlook
      • 6.3.2.1. Market Size & Forecast
        • 6.3.2.1.1. By Value
      • 6.3.2.2. Market Share & Forecast
        • 6.3.2.2.1. By Technology
        • 6.3.2.2.2. By Application
        • 6.3.2.2.3. By Modalities
        • 6.3.2.2.4. By End Use
    • 6.3.3. Mexico AI In Medical Imaging Market Outlook
      • 6.3.3.1. Market Size & Forecast
        • 6.3.3.1.1. By Value
      • 6.3.3.2. Market Share & Forecast
        • 6.3.3.2.1. By Technology
        • 6.3.3.2.2. By Application
        • 6.3.3.2.3. By Modalities
        • 6.3.3.2.4. By End Use

7. Europe AI In Medical Imaging Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Technology
    • 7.2.2. By Application
    • 7.2.3. By Modalities
    • 7.2.4. By End Use
    • 7.2.5. By Country
  • 7.3. Europe: Country Analysis
    • 7.3.1. Germany AI In Medical Imaging Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Technology
        • 7.3.1.2.2. By Application
        • 7.3.1.2.3. By Modalities
        • 7.3.1.2.4. By End Use
    • 7.3.2. France AI In Medical Imaging Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Technology
        • 7.3.2.2.2. By Application
        • 7.3.2.2.3. By Modalities
        • 7.3.2.2.4. By End Use
    • 7.3.3. United Kingdom AI In Medical Imaging Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecast
        • 7.3.3.2.1. By Technology
        • 7.3.3.2.2. By Application
        • 7.3.3.2.3. By Modalities
        • 7.3.3.2.4. By End Use
    • 7.3.4. Italy AI In Medical Imaging Market Outlook
      • 7.3.4.1. Market Size & Forecast
        • 7.3.4.1.1. By Value
      • 7.3.4.2. Market Share & Forecast
        • 7.3.4.2.1. By Technology
        • 7.3.4.2.2. By Application
        • 7.3.4.2.3. By Modalities
        • 7.3.4.2.4. By End Use
    • 7.3.5. Spain AI In Medical Imaging Market Outlook
      • 7.3.5.1. Market Size & Forecast
        • 7.3.5.1.1. By Value
      • 7.3.5.2. Market Share & Forecast
        • 7.3.5.2.1. By Technology
        • 7.3.5.2.2. By Application
        • 7.3.5.2.3. By Modalities
        • 7.3.5.2.4. By End Use

8. Asia Pacific AI In Medical Imaging Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Technology
    • 8.2.2. By Application
    • 8.2.3. By Modalities
    • 8.2.4. By End Use
    • 8.2.5. By Country
  • 8.3. Asia Pacific: Country Analysis
    • 8.3.1. China AI In Medical Imaging Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Technology
        • 8.3.1.2.2. By Application
        • 8.3.1.2.3. By Modalities
        • 8.3.1.2.4. By End Use
    • 8.3.2. India AI In Medical Imaging Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Technology
        • 8.3.2.2.2. By Application
        • 8.3.2.2.3. By Modalities
        • 8.3.2.2.4. By End Use
    • 8.3.3. Japan AI In Medical Imaging Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Technology
        • 8.3.3.2.2. By Application
        • 8.3.3.2.3. By Modalities
        • 8.3.3.2.4. By End Use
    • 8.3.4. South Korea AI In Medical Imaging Market Outlook
      • 8.3.4.1. Market Size & Forecast
        • 8.3.4.1.1. By Value
      • 8.3.4.2. Market Share & Forecast
        • 8.3.4.2.1. By Technology
        • 8.3.4.2.2. By Application
        • 8.3.4.2.3. By Modalities
        • 8.3.4.2.4. By End Use
    • 8.3.5. Australia AI In Medical Imaging Market Outlook
      • 8.3.5.1. Market Size & Forecast
        • 8.3.5.1.1. By Value
      • 8.3.5.2. Market Share & Forecast
        • 8.3.5.2.1. By Technology
        • 8.3.5.2.2. By Application
        • 8.3.5.2.3. By Modalities
        • 8.3.5.2.4. By End Use

9. Middle East & Africa AI In Medical Imaging Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Technology
    • 9.2.2. By Application
    • 9.2.3. By Modalities
    • 9.2.4. By End Use
    • 9.2.5. By Country
  • 9.3. Middle East & Africa: Country Analysis
    • 9.3.1. Saudi Arabia AI In Medical Imaging Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Technology
        • 9.3.1.2.2. By Application
        • 9.3.1.2.3. By Modalities
        • 9.3.1.2.4. By End Use
    • 9.3.2. UAE AI In Medical Imaging Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Technology
        • 9.3.2.2.2. By Application
        • 9.3.2.2.3. By Modalities
        • 9.3.2.2.4. By End Use
    • 9.3.3. South Africa AI In Medical Imaging Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Technology
        • 9.3.3.2.2. By Application
        • 9.3.3.2.3. By Modalities
        • 9.3.3.2.4. By End Use

10. South America AI In Medical Imaging Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Technology
    • 10.2.2. By Application
    • 10.2.3. By Modalities
    • 10.2.4. By End Use
    • 10.2.5. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil AI In Medical Imaging Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Technology
        • 10.3.1.2.2. By Application
        • 10.3.1.2.3. By Modalities
        • 10.3.1.2.4. By End Use
    • 10.3.2. Colombia AI In Medical Imaging Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Technology
        • 10.3.2.2.2. By Application
        • 10.3.2.2.3. By Modalities
        • 10.3.2.2.4. By End Use
    • 10.3.3. Argentina AI In Medical Imaging Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Technology
        • 10.3.3.2.2. By Application
        • 10.3.3.2.3. By Modalities
        • 10.3.3.2.4. By End Use

11. Market Dynamics

  • 11.1. Drivers
  • 11.2. Challenges

12. Market Trends & Developments

  • 12.1. Merger & Acquisition (If Any)
  • 12.2. Product Launches (If Any)
  • 12.3. Recent Developments

13. Global AI In Medical Imaging Market: SWOT Analysis

14. Porter's Five Forces Analysis

  • 14.1. Competition in the Industry
  • 14.2. Potential of New Entrants
  • 14.3. Power of Suppliers
  • 14.4. Power of Customers
  • 14.5. Threat of Substitute Products

15. Competitive Landscape

  • 15.1. Digital Diagnostics Inc.
    • 15.1.1. Business Overview
    • 15.1.2. Products & Services
    • 15.1.3. Recent Developments
    • 15.1.4. Key Personnel
    • 15.1.5. SWOT Analysis
  • 15.2. Tempus AI, Inc.
  • 15.3. Advanced Micro Devices, Inc.
  • 15.4. HeartFlow, Inc.
  • 15.5. Enlitic, Inc.
  • 15.6. Viz.ai, Inc.
  • 15.7. EchoNous Inc.
  • 15.8. HeartVista Inc.
  • 15.9. Exo Imaging, Inc.
  • 15.10. Nano-X Imaging Ltd.

16. Strategic Recommendations

17. About Us & Disclaimer