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美國人工智慧眼科診斷設備市場規模、佔有率和趨勢分析報告：按組件、應用、最終用途和細分市場預測（2026-2033 年）

U.S. AI-enabled Ophthalmic Diagnostic Devices Market Size, Share & Trends Analysis Report By Cmponent, By Application, By End Use, And Segment Forecasts, 2026 - 2033
出版日期: | 出版商: Grand View Research | 英文 60 Pages | 商品交期: 2-10個工作天內

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美國人工智慧眼科診斷設備市場概述

預計到 2025 年，美國人工智慧眼科診斷設備市場規模將達到 6,430 萬美元，到 2026 年將成長至 7,250 萬美元，到 2033 年將擴大至 2.672 億美元，2026 年至 2033 年的複合年成長率為 20.5%。

隨著醫療服務提供者加強對人工智慧的應用力度，以滿足日益成長的視網膜疾病早期檢測需求、提高篩檢效率並解決基層醫療機構眼科醫師短缺的問題，該市場正經歷快速成長。人工智慧驅動的視網膜成像系統正從決策支援工具發展成為無需專家解讀即可識別糖尿病視網膜病變和其他致盲疾病的自主診斷平台。

市場成長的主要促進因素之一是美國糖尿病和糖尿病視網膜病變（DR）盛行率的不斷上升，這使得擴充性的篩檢解決方案的需求顯著增加。根據美國疾病管制與預防中心（CDC）的視覺和眼部健康監測系統（VEHSS）的數據，2021年美國約有960萬人患有糖尿病視網膜病變，其中約184萬人患有威脅視力的糖尿病視網膜病變。預計到2050年，這一盛行率將顯著上升，預計將有1470萬美國人受到影響。這凸顯了美國糖尿病相關視力障礙負擔的日益惡化。這種不斷增加的疾病負擔正促使醫療保健系統採用人工智慧驅動的視網膜篩檢技術，這些技術可以提高基層醫療機構的篩檢率，同時準確識別需要轉診至專科醫生的患者。

技術創新和FDA的持續批准正進一步加速市場擴張。 2024年5月，FDA批准了Optomed公司的「Aurora」手持式眼底攝影機，整合了AEYE Health公司的自主人工智慧軟體（AEYE-DS）。這使得在美國幾乎所有醫療機構都能進行攜帶式糖尿病視網膜病變篩檢。由於此手持系統可在約一分鐘內完成自主影像分析，因此現在不僅可以在傳統的眼科診所進行篩檢，還可以在基層醫療醫療機構、藥房和社區健康中心進行篩檢。此次批准顯著擴大了人工智慧驅動的眼科診斷的普及範圍，並加強了攜帶式視網膜成像解決方案在美國的商業化進程。

此外，人工智慧驅動的攜帶式篩檢解決方案正日益支持基層醫療機構的早期檢測，減少對專科醫生的依賴，同時擴大服務不足和偏遠地區的視力保健覆蓋範圍。這些創新正在強化自主視網膜診斷在糖尿病常規管理和預防醫學中的作用。為了進一步推動這一趨勢，德州大學德克薩斯健康科學中心的研究人員在 ENDO 2025 會議上展示了「簡易行動人工智慧視網膜追蹤器 (SMART)」。這款由人工智慧驅動的攜帶式視網膜篩檢應用程式能夠在不到一秒的時間內以超過 99% 的準確率檢測和分期糖尿病視網膜病變。該解決方案可在包括智慧型手機在內的連網裝置上運行，使基層醫療提供者能夠將視網膜篩檢納入糖尿病常規護理，並在專科醫生難以到達的地區擴大高品質眼科檢查的覆蓋範圍。

此外，市場正受益於臨床實踐中日益成長的認可度以及糖尿病護理指南的支持。美國糖尿病協會 (ADA) 發布的《2025 年治療指南》認可了 FDA 批准的自主人工智慧系統，例如 AEYE-DS（AEYE Health 公司）、EyeArt（Eyenuk 公司）和 LumineticsCore（Digital Diagnostics 公司），認為在正確實施的情況下，這些系統可以有效替代糖尿病視網膜篩檢。該指南特別建議使用 FDA 批准的人工智慧演算法進行遠端影像判讀或視網膜攝影，以提高糖尿病視網膜病變篩檢的可近性，尤其是在眼科醫師資源有限的地區。

此外，美國糖尿病協會（ADA）指出，前瞻性多中心臨床試驗已證實了這些自主人工智慧平台的診斷準確性，支持將其應用於糖尿病常規診療。這些人工智慧篩檢服務也已納入美國大多數醫療保險計劃的承保範圍，進一步降低了採用這些服務的經濟門檻，並促進了其在基層醫療和內分泌科的更廣泛應用。隨著醫療服務提供者不斷重視預防醫學、疾病早期檢測和營運流程自動化，人工智慧眼科診斷設備有望在美國改善視力保健方面發揮日益重要的作用。

目錄

第1章：調查方法和範圍

第2章執行摘要

第3章：美國人工智慧眼科診斷設備市場：變數、趨勢和範圍

  • 市場譜系展望
  • 市場動態
  • 美國人工智慧驅動的眼科診斷設備市場分析工具

第4章：美國人工智慧眼科診斷設備市場：按組件分類的估算和趨勢分析

  • 美國人工智慧眼科診斷設備市場：基於組件的趨勢分析
  • 美國人工智慧眼科診斷設備市場：按組件分類，展望
  • 市場規模、預測與趨勢分析，2021-2033年
  • 眼底攝影機
  • OCT/OCTA系統
  • 超廣角成像系統
  • 裂隙燈成像系統

第5章：美國人工智慧眼科診斷設備市場：基於應用的估算與趨勢分析

  • 美國人工智慧眼科診斷設備市場：按應用領域分類的趨勢分析
  • 美國人工智慧眼科診斷設備市場：按應用和前景分類
  • 市場規模、預測與趨勢分析，2021-2033年
  • 糖尿病視網膜病變的檢測
  • 老齡化黃斑部病變（AMD）
  • 青光眼檢測
  • 糖尿病黃斑部水腫
  • 其他

第6章：美國人工智慧眼科診斷設備市場：按最終用途分類的估算和趨勢分析

  • 美國人工智慧眼科診斷設備市場：按最終用途分類的趨勢分析
  • 美國人工智慧眼科診斷設備市場：按最終用途分類，展望
  • 市場規模、預測與趨勢分析，2021-2033年
  • 醫院
  • 專科診所
  • 診斷中心
  • 居家照護
  • 學術機構

第7章 競爭情勢

  • 參與企業的分類
  • 主要公司簡介
    • Digital Diagnostics Inc.
    • Eyenuk, Inc.
    • AEYE Health
    • Optos
    • Notal Vision, Inc.
    • Carl Zeiss AG
    • Canon Medical Systems
    • Topcon Corporation
    • Optomed
    • Heidelberg Engineering
Product Code: GVR-4-68040-934-2

U.S. AI-enabled Ophthalmic Diagnostic Devices Market Summary

The U.S. AI-enabled ophthalmic diagnostic devices market size was valued at USD 64.3 million in 2025 and is projected to grow from USD 72.5 million in 2026 to USD 267.2 million by 2033, at a CAGR of 20.5% from 2026 to 2033. The market is experiencing rapid growth as healthcare providers increasingly adopt artificial intelligence to address rising demand for early detection of retinal diseases, improve screening efficiency, and overcome shortages of ophthalmologists in primary care settings. AI-enabled retinal imaging systems have evolved from decision-support tools to autonomous diagnostic platforms capable of identifying diabetic retinopathy and other sight-threatening diseases without specialist interpretation.

One of the primary drivers of market growth is the increasing prevalence of diabetes and diabetic retinopathy (DR) across the U.S., creating a substantial need for scalable screening solutions. According to the CDC's Vision and Eye Health Surveillance System (VEHSS), an estimated 9.6 million Americans were living with diabetic retinopathy in 2021, including approximately 1.84 million individuals with vision-threatening diabetic retinopathy. The prevalence is projected to increase substantially, with 14.7 million Americans expected to be affected by 2050, highlighting the growing burden of diabetes-related vision impairment in the U.S. This growing disease burden is encouraging healthcare systems to implement AI-enabled retinal screening technologies that can accurately identify patients requiring specialist referral while improving screening compliance in primary care settings.

Technological innovation and continued FDA clearances are further accelerating market expansion. In May 2024, the FDA cleared the Optomed Aurora handheld fundus camera integrated with AEYE Health's autonomous AI software (AEYE-DS), enabling portable diabetic retinopathy screening in virtually any healthcare setting across the U.S. The handheld system performs autonomous image analysis within approximately one minute, allowing screening to move beyond traditional eye clinics into primary care offices, pharmacies, and community health centers. This approval significantly broadened the accessibility of AI-enabled ophthalmic diagnostics and strengthened the commercialization of portable retinal imaging solutions in the U.S.

Moreover, AI-powered portable screening solutions are increasingly supporting early detection in primary care settings, reducing dependence on specialist availability while expanding access to vision care in underserved and remote communities. These innovations are strengthening the role of autonomous retinal diagnostics within routine diabetes management and preventive healthcare. To strengthen this trend, research presented at ENDO 2025 by investigators from the University of Texas Health Science Center at Houston introduced the Simple Mobile AI Retina Tracker (SMART), an AI-powered mobile retinal screening application capable of detecting and staging diabetic retinopathy with more than 99% accuracy in under one second. Designed to operate on internet-enabled devices, including basic smartphones, the solution enables primary care providers to incorporate retinal screening into routine diabetes care while expanding access to high-quality ophthalmic assessments in regions with limited specialist availability.

The market is also benefiting from growing clinical acceptance and supportive diabetes care guidelines. The American Diabetes Association (ADA) Standards of Care 2025 recognize FDA-authorized autonomous AI systems, including AEYE-DS (AEYE Health), EyeArt (Eyenuk), and LumineticsCore (Digital Diagnostics), as validated alternatives for diabetic retinopathy screening when appropriately implemented. The guidelines specifically recommend the use of retinal photography with remote reading or FDA-authorized AI algorithms to improve access to diabetic retinopathy screening, particularly in settings where access to eye care specialists is limited.

In addition, the ADA notes that prospective multicenter clinical trials have demonstrated the diagnostic accuracy of each of these autonomous AI platforms, supporting their integration into routine diabetes care. These AI-enabled screening services are also covered by most U.S. insurance plans, further reducing financial barriers to adoption and facilitating broader implementation across primary care and endocrinology practices. As healthcare providers continue to prioritize preventive care, early disease detection, and workflow automation, AI-enabled ophthalmic diagnostic devices are expected to play an increasingly important role in improving vision care outcomes across the U.S.

U.S. AI-enabled Ophthalmic Diagnostic Devices Market Report Segmentation

This report forecasts revenue growth and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the U.S. AI-enabled ophthalmic diagnostic devices market report based on component, application, and end use:

  • Component Outlook (Revenue, USD Unit, 2021 - 2033)
  • Fundus Cameras
  • OCT/OCTA Systems
  • Ultra-widefield Imaging Systems
  • Slit Lamp Imaging Systems
  • Application Outlook (Revenue, USD Unit, 2021 - 2033)
  • Diabetic Retinopathy Detection
  • Age-related Macular Degeneration (AMD)
  • Glaucoma Detection
  • Diabetic Macular Edema
  • Others
  • End Use Outlook (Revenue, USD Unit, 2021 - 2033)
  • Hospitals
  • Specialty Clinics
  • Diagnostic Centers
  • Home Care
  • Academic Centers

Table of Contents

Chapter 1. Methodology and Scope

  • 1.1. Market Segmentation and Scope
  • 1.2. Segment Definitions
    • 1.2.1. Component
    • 1.2.2. Application
    • 1.2.3. End Use
    • 1.2.4. Country scope
    • 1.2.5. Estimates and forecasts timeline
  • 1.3. Research Methodology
  • 1.4. Information Procurement
    • 1.4.1. Purchased database
    • 1.4.2. GVR's internal database
    • 1.4.3. Secondary sources
    • 1.4.4. Primary research
    • 1.4.5. Details of primary research
      • 1.4.5.1. Data for primary interviews in North America
  • 1.5. Information or Data Analysis
    • 1.5.1. Data analysis models
  • 1.6. Market Formulation & Validation
  • 1.7. Model Details
    • 1.7.1. Commodity flow analysis (Model 1)
    • 1.7.2. Approach 1: Commodity flow approach
    • 1.7.3. Volume price analysis (Model 2)
    • 1.7.4. Approach 2: Volume price analysis
  • 1.8. List of Secondary Sources
  • 1.9. List of Primary Sources
  • 1.10. Objectives

Chapter 2. Executive Summary

  • 2.1. Market Outlook
  • 2.2. Segment Outlook
    • 2.2.1. Component outlook
    • 2.2.2. Application outlook
    • 2.2.3. End Use outlook
    • 2.2.4. Country outlook
  • 2.3. Competitive Insights

Chapter 3. U.S. AI-enabled Ophthalmic Diagnostic Devices Market Variables, Trends & Scope

  • 3.1. Market Lineage Outlook
    • 3.1.1. Parent Market Outlook
    • 3.1.2. Related/ancillary market outlook
  • 3.2. Market Dynamics
    • 3.2.1. Market Driver Analysis
    • 3.2.2. Market Restraint Analysis
  • 3.3. U.S. AI-enabled Ophthalmic Diagnostic Devices Market Analysis Tools
    • 3.3.1. Industry Analysis - Porter's
      • 3.3.1.1. Bargaining power of suppliers
      • 3.3.1.2. Bargaining power of buyers
      • 3.3.1.3. Threat of substitutes
      • 3.3.1.4. Threat of new entrants
      • 3.3.1.5. Competitive rivalry
    • 3.3.2. PESTEL Analysis
      • 3.3.2.1. Political landscape
      • 3.3.2.2. Economic landscape
      • 3.3.2.3. Social landscape
      • 3.3.2.4. Technological landscape
      • 3.3.2.5. Environmental landscape
      • 3.3.2.6. Legal landscape

Chapter 4. U.S. AI-enabled Ophthalmic Diagnostic Devices Market: Component Estimates & Trend Analysis

  • 4.1. Segment Dashboard
  • 4.2. U.S. AI-enabled Ophthalmic Diagnostic Devices Market: Component Movement Analysis
  • 4.3. U.S. AI-enabled Ophthalmic Diagnostic Devices Market by Component Outlook (USD Million)
  • 4.4. Market Size & Forecasts and Trend Analyses, 2021 to 2033 for the following
  • 4.5. Fundus Cameras
    • 4.5.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)
  • 4.6. OCT/OCTA Systems
    • 4.6.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)
  • 4.7. Ultra-widefield Imaging Systems
    • 4.7.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)
  • 4.8. Slit Lamp Imaging Systems
    • 4.8.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)

Chapter 5. U.S. AI-enabled Ophthalmic Diagnostic Devices Market: Application Estimates & Trend Analysis

  • 5.1. Segment Dashboard
  • 5.2. U.S. AI-enabled Ophthalmic Diagnostic Devices Market: Application Movement Analysis
  • 5.3. U.S. AI-enabled Ophthalmic Diagnostic Devices Market by Application Outlook (USD Million)
  • 5.4. Market Size & Forecasts and Trend Analyses, 2021 to 2033 for the following
  • 5.5. Diabetic Retinopathy Detection
    • 5.5.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)
  • 5.6. Age-related Macular Degeneration (AMD)
    • 5.6.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)
  • 5.7. Glaucoma Detection
    • 5.7.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)
  • 5.8. Diabetic Macular Edema
    • 5.8.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)
  • 5.9. Others
    • 5.9.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)

Chapter 6. U.S. AI-enabled Ophthalmic Diagnostic Devices Market: End Use Estimates & Trend Analysis

  • 6.1. Segment Dashboard
  • 6.2. U.S. AI-enabled Ophthalmic Diagnostic Devices Market: End Use Movement Analysis
  • 6.3. U.S. AI-enabled Ophthalmic Diagnostic Devices Market by End Use Outlook (USD Million)
  • 6.4. Market Size & Forecasts and Trend Analyses, 2021 to 2033 for the following
  • 6.5. Hospitals
    • 6.5.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)
  • 6.6. Specialty Clinics
    • 6.6.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)
  • 6.7. Diagnostic Centers
    • 6.7.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)
  • 6.8. Home Care
    • 6.8.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)
  • 6.9. Academic Centers
    • 6.9.1. Market Revenue Estimates and Forecasts, 2021 - 2033 (USD Million)

Chapter 7. Competitive Landscape

  • 7.1. Market Participant Categorization
  • 7.2. Key Company Profiles
    • 7.2.1. Digital Diagnostics Inc.
      • 7.2.1.1. Company Overview
      • 7.2.1.2. Financial Performance
      • 7.2.1.3. Product/Service Benchmarking
      • 7.2.1.4. Strategic Initiatives
    • 7.2.2. Eyenuk, Inc.
      • 7.2.2.1. Company Overview
      • 7.2.2.2. Financial Performance
      • 7.2.2.3. Product/Service Benchmarking
      • 7.2.2.4. Strategic Initiatives
    • 7.2.3. AEYE Health
      • 7.2.3.1. Company Overview
      • 7.2.3.2. Financial Performance
      • 7.2.3.3. Product/Service Benchmarking
      • 7.2.3.4. Strategic Initiatives
    • 7.2.4. Optos
      • 7.2.4.1. Company Overview
      • 7.2.4.2. Financial Performance
      • 7.2.4.3. Product/Service Benchmarking
      • 7.2.4.4. Strategic Initiatives
    • 7.2.5. Notal Vision, Inc.
      • 7.2.5.1. Company Overview
      • 7.2.5.2. Financial Performance
      • 7.2.5.3. Product/Service Benchmarking
      • 7.2.5.4. Strategic Initiatives
    • 7.2.6. Carl Zeiss AG
      • 7.2.6.1. Company Overview
      • 7.2.6.2. Financial Performance
      • 7.2.6.3. Product/Service Benchmarking
      • 7.2.6.4. Strategic Initiatives
    • 7.2.7. Canon Medical Systems
      • 7.2.7.1. Company Overview
      • 7.2.7.2. Financial Performance
      • 7.2.7.3. Product/Service Benchmarking
      • 7.2.7.4. Strategic Initiatives
    • 7.2.8. Topcon Corporation
      • 7.2.8.1. Company Overview
      • 7.2.8.2. Financial Performance
      • 7.2.8.3. Product/Service Benchmarking
      • 7.2.8.4. Strategic Initiatives
    • 7.2.9. Optomed
      • 7.2.9.1. Company Overview
      • 7.2.9.2. Financial Performance
      • 7.2.9.3. Product/Service Benchmarking
      • 7.2.9.4. Strategic Initiatives
    • 7.2.10. Heidelberg Engineering
      • 7.2.10.1. Company Overview
      • 7.2.10.2. Financial Performance
      • 7.2.10.3. Product/Service Benchmarking
      • 7.2.10.4. Strategic Initiatives

List of Tables

  • Table 1. List of secondary sources
  • Table 2. List of abbreviations
  • Table 3. U.S. AI-enabled ophthalmic diagnostic devices market, by component, 2021 - 2033 (USD Million)
  • Table 4. U.S. AI-enabled ophthalmic diagnostic devices market, by application, 2021 - 2033 (USD Million)
  • Table 5. U.S. AI-enabled ophthalmic diagnostic devices market, by end use, 2021 - 2033 (USD Million)

List of Figures

  • Fig 1. U.S. AI-enabled ophthalmic diagnostic devices market segmentation
  • Fig 2. Market research process
  • Fig 3. Data triangulation techniques
  • Fig 4. Primary research pattern
  • Fig 5. Market research approaches
  • Fig 6. Value-chain-based sizing & forecasting
  • Fig 7. Market formulation & validation
  • Fig 8. Market snapshot
  • Fig 9. Cmponent and application outlook (USD Million)
  • Fig 10. End use outlook (USD Million)
  • Fig 11. Competitive landscape
  • Fig 12. U.S. AI-enabled ophthalmic diagnostic devices market dynamics
  • Fig 13. U.S. AI-enabled ophthalmic diagnostic devices market: Porter's five forces analysis
  • Fig 14. U.S. AI-enabled ophthalmic diagnostic devices market: PESTLE analysis
  • Fig 15. U.S. AI-enabled ophthalmic diagnostic devices market: Component segment dashboard
  • Fig 16. U.S. AI-enabled ophthalmic diagnostic devices market: Component market share analysis, 2025 & 2033
  • Fig 17. Fundus cameras market, 2021 - 2033 (USD Million)
  • Fig 18. OCT/OCTA systems market, 2021 - 2033 (USD Million)
  • Fig 19. Ultra-widefield imaging systems market, 2021 - 2033 (USD Million)
  • Fig 20. Slit lamp imaging systems market, 2021 - 2033 (USD Million)
  • Fig 21. U.S. AI-enabled ophthalmic diagnostic devices market: Application segment dashboard
  • Fig 22. U.S. AI-enabled ophthalmic diagnostic devices market: Application market share analysis, 2025 & 2033
  • Fig 23. Diabetic retinopathy detection market, 2021 - 2033 (USD Million)
  • Fig 24. Age-related macular degeneration (AMD) market, 2021 - 2033 (USD Million)
  • Fig 25. Glaucoma detection market, 2021 - 2033 (USD Million)
  • Fig 26. Diabetic macular edema market, 2021 - 2033 (USD Million)
  • Fig 27. Others market, 2021 - 2033 (USD Million)
  • Fig 28. U.S. AI-enabled ophthalmic diagnostic devices market: End use segment dashboard
  • Fig 29. U.S. AI-enabled ophthalmic diagnostic devices market: U.S. AI-enabled ophthalmic diagnostic devices market share analysis, 2025 & 2033
  • Fig 30. Hospitals market, 2021 - 2033 (USD Million)
  • Fig 31. Specialty clinics market, 2021 - 2033 (USD Million)
  • Fig 32. Diagnostic centers market, 2021 - 2033 (USD Million)
  • Fig 33. Home care market, 2021 - 2033 (USD Million)
  • Fig 34. Academic Centers market, 2021 - 2033 (USD Million)
  • Fig 35. Company categorization
  • Fig 36. Company market position analysis
  • Fig 37. Strategic framework