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1880433

人工智慧驅動的成像工作流程平台市場預測至2032年：按組件、模式、應用、最終用戶和地區分類的全球分析

AI-Powered Imaging Workflow Platforms Market Forecasts to 2032 - Global Analysis By Component, Modality, 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 的一項研究，全球 AI 驅動的影像工作流程平台市場預計到 2025 年將達到 11 億美元，到 2032 年將達到 78 億美元，在預測期內的複合年成長率為 33%。

人工智慧驅動的影像工作流程平台是軟硬體一體化的解決方案，利用人工智慧技術來管理、分析和解讀醫學影像資料。這些平台能夠自動執行諸如排班、影像路由、異常檢測和初步報告生成等任務，從而提高篩檢效率和診斷準確性。它們可以幫助放射科醫生和臨床醫生優先處理緊急病例，減輕行政工作量，並增強放射學和病理學領域的臨床決策能力。

根據國際清算銀行（BIS）的說法，分析多家銀行交易模式的聯盟人工智慧模型在檢測複雜的跨機構支付詐騙要有效得多。

對更有效率的放射科工作流程的需求日益成長

放射科面臨的日益成長的掃描量壓力，正推動人工智慧工作流程平台的普及。醫院正在尋求自動化分流、更快的影像路由和智慧化的工作負載平衡，以消除瓶頸並提高病患吞吐量。人工智慧工具可以縮短閱片時間、標記緊急病例，並與PACS/RIS平台無縫整合。隨著放射科醫師職業倦怠和人員短缺問題的日益嚴重，工作流程自動化已成為提升整個醫學影像生態系統效率、增強營運韌性和確保診斷一致性的關鍵。

不透明的人工智慧決策模型會降低臨床醫生的信任度。

人工智慧決策流程可解釋性不足是其應用的關鍵阻礙因素。這些過程通常如同“黑箱”，降低了臨床醫生對自動化建議的信任。放射科醫生需要透明的證據鏈、可解釋的輸出結果以及檢驗的推理過程，才能安全地將人工智慧融入他們的診斷流程中。監管機構日益重視可解釋性，並透過增加額外的檢驗層級來減緩人工智慧的普及應用。如果沒有一個健全的可解釋性框架，人工智慧工作流程平台將面臨臨床相關人員的質疑，尤其是在高風險的診斷環境中，課責和準確性至關重要。

多模態診斷整合

將包括影像、病理、基因組學和臨床記錄在內的多模態診斷數據整合到由人工智慧驅動的單一工作流程層中，蘊藏著巨大的機會。這種融合能夠實現全面的診斷推斷，使平台能夠提供更豐富、更具情境感知的洞察。多模態整合有助於早期疾病檢測，提高分診準確性，並支持個人化治療方案。隨著醫療保健朝著一體化診斷​​生態系統發展，能夠整合多樣化資料流的人工智慧解決方案至關重要，這也推動了對下一代影像工作流程平台的需求。

快速演算法過時

隨著影像技術、成像通訊協定和臨床標準的快速發展，許多人工智慧模型的重新訓練速度遠不及演算法更新換代的速度，演算法的快速過時構成了嚴重的威脅。過時的演算法會導致效能下降、漏診異常以及偏差漂移，從而損害臨床信任。供應商必須持續投資於資料集更新、監管檢驗和自適應學習基礎設施。未能及時更新演算法將導致競爭劣勢和平台可靠性下降，尤其對於那些尋求能夠持續最佳化性能、面向未來的人工智慧系統的醫院而言更是如此。

新冠疫情的影響：

新冠疫情加速了放射科服務的數位化，並顯著推動了人工智慧工作流程平台的應用，以滿足診斷影像需求的激增和現場人員減少的情況。人工智慧輔助的胸部CT和X光片分診對於快速評估新冠病情嚴重程度至關重要，並簡化了臨床決策流程。遠端閱片和雲端基礎的影像共用迅速發展，進一步鞏固了人們對自動化工作流程的長期興趣。疫情最終凸顯了人工智慧驅動的效率提升價值，並鞏固了這些平台作為後疫情時代放射科診療實踐中不可或缺的工具的地位。

預計在預測期內，軟體平台細分市場將佔據最大的市場佔有率。

由於人工智慧引擎的廣泛應用，軟體平台預計將佔據最大的市場佔有率。這些引擎能夠自動完成分診、影像優先排序、報告結構化和工作流程協調等工作。醫院正擴大採用與現有PACS/RIS系統對接的集中式平台，以最大限度地減少營運中斷。這些解決方案提供持續升級、可擴展的處理能力和跨模態相容性，構成了數位放射線生態系統的基礎。它們在整個診斷流程中的多功能性進一步鞏固了其在全球市場的領先地位。

預計在預測期內，MRI細分市場將實現最高的複合年成長率。

在預測期內，受縮短掃描時間和最佳化閱片流程需求的不斷成長的推動，磁振造影（MRI）領域預計將實現最高成長率。人工智慧平台透過自動化通訊協定選擇、降噪、分割和定量分析來提高MRI的吞吐量。 MRI在神經病學、腫瘤學和肌肉骨骼疾病領域的日益普及，推動了對人工智慧輔助工具的需求。人工智慧驅動的MRI加速和重建演算法進一步促進了其應用，使MRI成為工作流程平台使用者群體成長最快的領域。

佔比最大的地區：

預計亞太地區將在預測期內佔據最大的市場佔有率。這主要得益於診斷成像基礎設施的快速擴張、患者群體的不斷成長以及政府對人工智慧驅動的醫療現代化的大力支持。中國、日本、韓國和印度等國家正大力投資建造智慧醫院並數位化轉型。人工智慧創新中心的蓬勃發展以及雲端基礎成像平台的日益普及進一步鞏固了該地區的領先地位。這些因素共同推動了亞太地區醫療系統工作流程自動化技術的快速普及。

預計年複合成長率最高的地區：

在預測期內，北美預計將呈現最高的複合年成長率，這主要得益於該地區早期採用先進的放射學資訊技術系統、健全的人工智慧檢驗法規結構以及成熟的醫院數位化。主要人工智慧開發商的存在、對臨床自動化的巨額投資以及與PACS/RIS生態系統的廣泛整合，都在推動著這一成長。此外，對工作流程效率的日益重視、放射科醫生的短缺以及人工智慧輔助成像報銷途徑的不斷擴大，也進一步推動了該地區市場的快速擴張。

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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
    • 原始研究資料
    • 次級研究資訊來源
    • 先決條件

第3章 市場趨勢分析

  • 介紹
  • 促進要素
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的影響

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. 人工智慧影像工作流程平台市場（按組件分類）

  • 介紹
  • 軟體平台
  • 人工智慧分析模組
  • 工作流程最佳化引擎
  • 報告和視覺化工具
  • 整合和中介軟體解決方案

6. 依成像方式分類的AI驅動成像工作流程平台市場

  • 介紹
  • MRI
  • CT
  • 超音波
  • X光和透視
  • PET和核子醫學影像

7. 按應用分類的AI賦能影像工作流程平台市場

  • 介紹
  • 診斷工作流程自動化
  • 臨床決策支持
  • 影像分診和優先排序
  • 品管和減少錯誤
  • 放射學報告最佳化

8. 全球人工智慧驅動的影像工作流程平台市場（按最終用戶分類）

  • 介紹
  • 醫院
  • 診斷中心
  • 研究所
  • 人工智慧健康科技公司
  • 放射學團體和網路

9. 全球人工智慧驅動的影像工作流程平台市場（按地區分類）

  • 介紹
  • 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
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 亞太其他地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 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10章：重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與併購
  • 新產品上市
  • 業務拓展
  • 其他關鍵策略

第11章 企業概況

  • Siemens Healthineers
  • GE HealthCare
  • Philips
  • IBM
  • Nuance
  • Viz.ai
  • Aidoc
  • Zebra Medical Vision
  • Arterys
  • Agfa Healthcare
  • Qure.ai
  • Canon Medical
  • Fujifilm
  • Riverain Technologies
  • Imagen Technologies
  • Butterfly Network
Product Code: SMRC32472

According to Stratistics MRC, the Global AI-Powered Imaging Workflow Platforms Market is accounted for $1.1 billion in 2025 and is expected to reach $7.8 billion by 2032 growing at a CAGR of 33% during the forecast period. AI-powered imaging workflow platforms are integrated software and hardware solutions that use artificial intelligence to manage, analyze, and interpret medical imaging data. These platforms automate tasks such as scheduling, image routing, anomaly detection, and preliminary report generation, improving screening efficiency and diagnostic accuracy. They help radiologists and clinicians prioritize urgent cases, reduce administrative workload, and enhance clinical decision-making in radiology and pathology.

According to the Bank for International Settlements, consortium-based AI models that analyze transaction patterns across multiple banks are significantly more effective at detecting sophisticated, cross-institutional payment fraud.

Market Dynamics:

Driver:

Rising demand to streamline radiology workflows

Rising pressure on radiology departments to manage increasing scan volumes is driving strong adoption of AI-powered workflow platforms. Hospitals seek automated triage, faster image routing, and intelligent workload balancing to reduce bottlenecks and improve patient throughput. AI tools accelerate reading times, flag urgent cases, and integrate seamlessly with PACS/RIS platforms. As radiologists face rising burnout and staffing shortages, workflow automation becomes a mission-critical enabler of efficiency, operational resilience, and diagnostic consistency across medical imaging ecosystems.

Restraint:

Opaque AI decision models limiting clinician trust

A key restraint is the limited interpretability of AI decision pathways, which often function as "black boxes," reducing clinician confidence in automated recommendations. Radiologists require transparent evidence trails, explainable outputs, and validated reasoning to integrate AI into diagnostic routines safely. Regulatory bodies increasingly emphasize explainability, adding additional validation layers that slow adoption. Without robust interpretability frameworks, AI workflow platforms face hesitation from clinical stakeholders, especially in high-stakes diagnostic environments where accountability and accuracy are paramount.

Opportunity:

Integration of multimodal diagnostics

A major opportunity lies in unifying multimodal diagnostic data-integrating imaging, pathology, genomics, and clinical records into a single AI-powered workflow layer. This fusion enables holistic diagnostic reasoning, allowing platforms to deliver richer, more context-aware insights. Multimodal integration improves early disease detection, enhances triage precision, and supports personalized care pathways. As healthcare shifts toward unified diagnostic ecosystems, AI solutions capable of synthesizing diverse data streams become essential, driving demand for next-generation imaging workflow platforms.

Threat:

Rapid algorithm obsolescence

Rapid algorithm obsolescence poses a growing threat as imaging technologies, acquisition protocols, and clinical standards evolve faster than many AI models can be retrained. Outdated algorithms risk performance degradation, missed anomalies, or bias drift, eroding clinical trust. Vendors must invest continuously in dataset updates, regulatory revalidations, and adaptive learning infrastructures. Failure to maintain algorithm currency can result in competitive displacement and reduced platform reliability, especially in hospitals seeking future-proof AI systems with continuous performance optimization.

Covid-19 Impact:

COVID-19 accelerated the digitization of radiology services, significantly boosting adoption of AI workflow platforms to manage surging imaging demands and reduced onsite staffing. AI-enabled triage for chest CTs and X-rays became critical for rapid COVID severity assessment, streamlining clinical decision-making. Remote reading and cloud-based imaging collaboration expanded sharply, reinforcing long-term interest in automated workflows. The pandemic ultimately highlighted the value of AI-driven efficiency, cementing these platforms as essential tools in post-pandemic radiology operations.

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

The software platforms segment is expected to command the largest market share, resulting from widespread deployment of AI engines that automate triage, image prioritization, report structuring, and workflow orchestration. Hospitals increasingly adopt centralized platforms that integrate with existing PACS/RIS systems, minimizing operational disruption. These solutions provide continuous upgrades, scalable processing, and cross-modality compatibility, making them foundational to digital radiology ecosystems. Their versatility across diagnostic pathways further reinforces their leadership in the global market.

The MRI segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the MRI segment is predicted to witness the highest growth rate, propelled by the rising need to accelerate long scan times and optimize interpretation workflows. AI platforms enhance MRI throughput by automating protocol selection, noise reduction, segmentation, and quantitative analysis. As MRI usage grows in neurology, oncology, and musculoskeletal care, demand for AI support tools intensifies. AI-driven MRI acceleration and reconstruction algorithms further stimulate adoption, positioning this modality as the fastest-growing user base for workflow platforms.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share, attributed to rapid expansion of diagnostic imaging infrastructure, rising patient volumes, and strong government support for AI-driven healthcare modernization. Countries such as China, Japan, South Korea, and India are investing heavily in smart hospitals and radiology digitization. Growing AI innovation hubs and increasing adoption of cloud-based imaging platforms reinforce the region's dominance. These factors collectively accelerate deployment of workflow automation technologies across APAC healthcare systems.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR associated with early adoption of advanced radiology IT systems, strong regulatory frameworks for AI validation, and mature hospital digitization. The presence of leading AI developers, substantial investment in clinical automation, and widespread integration with PACS/RIS ecosystems accelerates growth. Rising focus on workflow efficiency, shortage of radiologists, and expanding reimbursement pathways for AI-supported imaging further support rapid market expansion in the region.

Key players in the market

Some of the key players in AI-Powered Imaging Workflow Platforms Market include Siemens Healthineers, GE HealthCare, Philips, IBM, Nuance, Viz.ai, Aidoc, Zebra Medical Vision, Arterys, Agfa Healthcare, Qure.ai, Canon Medical, Fujifilm, Riverain Technologies, Imagen Technologies, and Butterfly Network.

Key Developments:

In August 2025, GE HealthCare introduced the Edison Workflow Orchestrator, a vendor-agnostic platform that uses predictive AI to allocate reading assignments across a radiology department in real-time based on radiologist subspecialty, current workload, and exam complexity, reducing report turnaround times by over 20%.

In July 2025, Viz.ai received FDA clearance for its Viz TAVR platform, which uses AI to automatically analyze CT scans for structural heart disease, identify eligible patients for Transcatheter Aortic Valve Replacement (TAVR), and instantly notify the heart team, streamlining the pre-procedural workflow.

In June 2025, Philips announced the Enterprise Radiology Performance Suite, a cloud-native platform that leverages AI to provide health systems with a real-time dashboard of key performance indicators (KPIs), predicting bottlenecks and recommending resource shifts to optimize departmental efficiency.

Components Covered:

  • Software Platforms
  • AI Analytics Modules
  • Workflow Optimization Engines
  • Reporting & Visualization Tools
  • Integration & Middleware Solutions

Modalities Covered:

  • MRI
  • CT
  • Ultrasound
  • X-Ray & Fluoroscopy
  • PET & Nuclear Imaging

Applications Covered:

  • Diagnostic Workflow Automation
  • Clinical Decision Support
  • Image Triage & Prioritization
  • Quality Control & Error Reduction
  • Radiology Reporting Optimization

End Users Covered:

  • Hospitals
  • Diagnostic Centers
  • Research Institutions
  • AI Health-Tech Companies
  • Radiology Groups & Networks

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 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 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-Powered Imaging Workflow Platforms Market, By Component

  • 5.1 Introduction
  • 5.2 Software Platforms
  • 5.3 AI Analytics Modules
  • 5.4 Workflow Optimization Engines
  • 5.5 Reporting & Visualization Tools
  • 5.6 Integration & Middleware Solutions

6 Global AI-Powered Imaging Workflow Platforms Market, By Modality

  • 6.1 Introduction
  • 6.2 MRI
  • 6.3 CT
  • 6.4 Ultrasound
  • 6.5 X-Ray & Fluoroscopy
  • 6.6 PET & Nuclear Imaging

7 Global AI-Powered Imaging Workflow Platforms Market, By Application

  • 7.1 Introduction
  • 7.2 Diagnostic Workflow Automation
  • 7.3 Clinical Decision Support
  • 7.4 Image Triage & Prioritization
  • 7.5 Quality Control & Error Reduction
  • 7.6 Radiology Reporting Optimization

8 Global AI-Powered Imaging Workflow Platforms Market, By End User

  • 8.1 Introduction
  • 8.2 Hospitals
  • 8.3 Diagnostic Centers
  • 8.4 Research Institutions
  • 8.5 AI Health-Tech Companies
  • 8.6 Radiology Groups & Networks

9 Global AI-Powered Imaging Workflow Platforms Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 Siemens Healthineers
  • 11.2 GE HealthCare
  • 11.3 Philips
  • 11.4 IBM
  • 11.5 Nuance
  • 11.6 Viz.ai
  • 11.7 Aidoc
  • 11.8 Zebra Medical Vision
  • 11.9 Arterys
  • 11.10 Agfa Healthcare
  • 11.11 Qure.ai
  • 11.12 Canon Medical
  • 11.13 Fujifilm
  • 11.14 Riverain Technologies
  • 11.15 Imagen Technologies
  • 11.16 Butterfly Network

List of Tables

  • Table 1 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Region (2024-2032) ($MN) HeartFlow
  • Table 2 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Software Platforms (2024-2032) ($MN) Sectra
  • Table 4 Global AI-Powered Imaging Workflow Platforms Market Outlook, By AI Analytics Modules (2024-2032) ($MN)
  • Table 5 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Workflow Optimization Engines (2024-2032) ($MN)
  • Table 6 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Reporting & Visualization Tools (2024-2032) ($MN)
  • Table 7 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Integration & Middleware Solutions (2024-2032) ($MN)
  • Table 8 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Modality (2024-2032) ($MN)
  • Table 9 Global AI-Powered Imaging Workflow Platforms Market Outlook, By MRI (2024-2032) ($MN)
  • Table 10 Global AI-Powered Imaging Workflow Platforms Market Outlook, By CT (2024-2032) ($MN)
  • Table 11 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Ultrasound (2024-2032) ($MN)
  • Table 12 Global AI-Powered Imaging Workflow Platforms Market Outlook, By X-Ray & Fluoroscopy (2024-2032) ($MN)
  • Table 13 Global AI-Powered Imaging Workflow Platforms Market Outlook, By PET & Nuclear Imaging (2024-2032) ($MN)
  • Table 14 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Application (2024-2032) ($MN)
  • Table 15 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Diagnostic Workflow Automation (2024-2032) ($MN)
  • Table 16 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Clinical Decision Support (2024-2032) ($MN)
  • Table 17 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Image Triage & Prioritization (2024-2032) ($MN)
  • Table 18 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Quality Control & Error Reduction (2024-2032) ($MN)
  • Table 19 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Radiology Reporting Optimization (2024-2032) ($MN)
  • Table 20 Global AI-Powered Imaging Workflow Platforms Market Outlook, By End User (2024-2032) ($MN)
  • Table 21 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Hospitals (2024-2032) ($MN)
  • Table 22 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Diagnostic Centers (2024-2032) ($MN)
  • Table 23 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Research Institutions (2024-2032) ($MN)
  • Table 24 Global AI-Powered Imaging Workflow Platforms Market Outlook, By AI Health-Tech Companies (2024-2032) ($MN)
  • Table 25 Global AI-Powered Imaging Workflow Platforms Market Outlook, By Radiology Groups & Networks (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.