查看購物車
  • English
  • Japanese
  • Korean
封面
市場調查報告書
商品編碼
2065220

人工智慧病理解決方案市場預測至2034年：全球分析（按組件、部署模式、技術、病理類型、治療領域、最終用戶和地區分類）

AI-Based Pathology Solutions Market Forecasts to 2034 - Global Analysis By Component (Component, Hardware, and Services), Deployment Mode, Technology, Pathology Type, Therapeutic Area, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球人工智慧病理診斷市場預計將在 2026 年達到 18 億美元，到 2034 年達到 72 億美元，在預測期內以 18.9% 的複合年成長率成長。

人工智慧病理解決方案是指利用人工智慧、機器學習和電腦視覺演算法來提高病理分析的準確性、效率和擴充性的軟硬體平台。這些解決方案將玻璃組織切片數位化為高解析度全切片影像，並應用深度學習模型來檢測、量化和分類與癌症診斷、預後和治療反應評估相關的細胞形態、生物標記和組織模式。

全球病理學家嚴重人手不足，癌症診斷數量卻不斷增加。

尤其是在新興市場和農村醫療環境中，訓練有素的病理學家嚴重短缺且日益嚴重，加上癌症診斷數量呈指數級成長，迫切需要人工智慧驅動的病理工作流程。傳統的切片人工閱片耗時費力，且容易出現觀察者間差異，導致癌症患者診斷及治療延誤。以人工智慧為基礎的影像分析平台透過自動化常規篩檢，提供了一種高度可擴展的解決方案，使擴充性能夠更快地進行閱片，並優先處理高風險病例，同時提供定量生物標記評估，從而減少主觀解讀差異。這種實際需求是推動市場快速發展的主要動力。

數位病理學和人工智慧輔助病理學服務的報銷限額有限。

儘管人工智慧病理平台已展現出顯著的臨床和營運優勢，但在大多數醫療體系中，數位病理和人工智慧輔助診斷服務的報銷機制仍不清楚。包括美國和歐洲在內的主要市場缺乏針對人工智慧病理診斷的特定計費代碼，這給實驗室帶來了巨大的經濟障礙，因為整合全切片成像基礎設施和人工智慧軟體需要大量的資本投入。由於缺乏清晰的收入確認途徑，實驗室管理者難以建立合理的商業案例來證明從傳統的顯微鏡工作流程過渡到人工智慧病理的必要性，從而限制了市場接受度。

伴隨診斷和生物標記定量應用的擴展

免疫療法和標靶癌症療法對伴隨診斷的日益依賴，為能夠自動從組織切片中定量分析生物標記的基於人工智慧的病理平台帶來了巨大的發展機會。人工智慧演算法能夠以高於人工評估的重複性，對PD-L1表達、HER2評分、腫瘤浸潤淋巴細胞密度和其他治療預測性生物標記進行一致且高通量的定量分析。隨著需要伴隨診斷的已通過核准癌症治療方法數量的成長，藥物研發和臨床腫瘤學領域對能夠實現標準化、擴充性和可審計的生物標記分析的人工智慧病理診斷工具的需求預計將顯著增加。

人工智慧診斷演算法的檢驗挑戰與監管不確定性

人工智慧病理演算法在能夠可靠地應用於臨床之前，需要在不同的患者群體、組織類型和染色方案中進行嚴格的臨床檢驗。在不同的檢查室環境和不同的預分析物條件下展現其通用性，面臨巨大的技術和監管挑戰。儘管FDA和EMA等監管機構正在製定基於人工智慧的醫療設備軟體框架，但監管指導的製定速度落後於演算法創新的速度，這給製造商帶來了核准方面的不確定性。此外，由於訓練資料中演算法偏差導致的系統性診斷錯誤風險，可能會給開發者帶來重大的法律責任，並削弱臨床對人工智慧病理診斷工具的信心。

新型冠狀病毒（COVID-19）的影響：

新冠疫情導致病理檢查室人員短缺、傳染病檢查優先進行以及非緊急癌症篩檢計畫延誤，從而擾亂了病理實驗室的正常運作，暫時抑制了對人工智慧病理解決方案的需求。然而，疫情也凸顯了依賴現場操作和人工流程的病理工作流程的脆弱性，進一步加速了數位轉型的必要性。遠距病理診斷，尤其是全切片影像和人工智慧輔助分診技術，在疫情封鎖期間展現出強大的適應能力，促使醫療機構更積極地投資建立永久性數位病理基礎設施。疫情後癌症篩檢率的回升，也使得能夠有效解決診斷延誤問題的AI工具維持了強勁的需求。

在預測期內，軟體領域預計將佔據最大的市場佔有率。

預計在預測期內，軟體領域將佔據最大的市場佔有率。影像分析軟體、工作流程管理平台和診斷支援工具是人工智慧病理生態系統中最有價值的組成部分，它們為檢查室和製藥研究機構帶來了豐厚的訂閱和授權收入。演算法的持續改進、目標組織類型的擴展以及與實驗室資訊系統 (LIS) 的整合，都支撐著軟體需求。向 SaaS 交付模式的轉變擴大了軟體的獲取途徑，使即使是小規模檢查室也能採用人工智慧病理功能，而無需進行大規模的基礎設施投資。

預計深度學習領域在預測期內將呈現最高的複合年成長率。

在預測期內，深度學習領域預計將呈現最高的成長率。深度學習卷積類神經網路在檢測與癌症相關的細微組織學模式方面展現出卓越的性能，不僅優於傳統的機器學習方法，在某些診斷任務中甚至超越了病理專家。用於模型訓練的大規模帶標註數位病理資料集的日益豐富，以及計算硬體的進步使得高效的神經網路推理成為可能，這些因素正在加速深度學習在臨床和研究領域的應用，例如腫瘤分類、惡性程度分級和生物標記定量等任務。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率。該地區受益於成熟的數位病理基礎設施、高癌症發病率帶來的持續診斷需求，以及製藥業對用於藥物研發的計算病理學的大力投資。主要的AI病理公司總部主要位於美國，早期滲透美國國內市場被認為是必要的。 FDA對AI診斷軟體的積極監管反應，以及日益嚴格的檢查室認證要求（強調品質和可重複性），預計將有助於北美保持市場領先地位。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率。全部區域癌症發生率的快速成長，以及印度和中國等國家病理學家嚴重短缺，正推動著對人工智慧診斷工具的迫切需求。政府主導的數位化醫療現代化舉措以及醫院網路對全切片成像基礎設施的加大投入，共同創造了有利的市場環境。韓國和日本憑藉其先進的醫療技術應用水平，也為該地區人工智慧病理市場的成長做出了顯著貢獻，尤其是在研究和製藥領域。

免費客製化服務：

所有購買此報告的客戶均可享受以下免費自訂選項之一：

  • 企業概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 對主要公司進行SWOT分析（最多3家公司）
  • 區域分類
    • 根據客戶要求，我們可以提供主要國家的市場估算和預測，以及複合年成長率（註：需經可行性確認）。
  • 競爭性標竿分析
    • 根據產品系列、地理覆蓋範圍和策略聯盟對領先公司進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 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
    • 競爭公司之間的競爭
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章：全球人工智慧病理解決方案市場：按組件分類

  • 軟體
    • 影像分析軟體
    • 工作流程管理軟體
    • 診斷支援軟體
    • 預測分析軟體
  • 硬體
    • 全幻燈片成像掃描儀
    • 伺服器和儲存系統
    • 高效能運算基礎設施
  • 服務
    • 諮詢服務
    • 整合和配置服務
    • 維護和支援服務
    • 培訓服務

第6章 全球人工智慧病理解決方案市場：按部署模式分類

  • 現場
  • 基於雲端的
  • 混合實現

第7章 全球人工智慧病理解決方案市場：按技術分類

  • 機器學習（ML）
  • 深度學習
  • 電腦視覺
  • 自然語言處理（NLP）
  • 預測分析

第8章：全球人工智慧病理解決方案市場：按病理類型分類

  • 解剖病理學
  • 臨床病理
  • 分子病理學
  • 數位病理學

第9章 全球人工智慧病理解決方案市場：按治療領域分類

  • 腫瘤學
  • 神經病學
  • 心血管疾病
  • 感染疾病
  • 皮膚科
  • 消化系統疾病
  • 呼吸系統疾病
  • 其他治療領域

第10章：全球人工智慧病理解決方案市場：按最終用戶分類

  • 醫院
  • 診斷檢查室
  • 學術研究機構
  • 製藥和生物技術公司
  • 受託研究機構（CRO）

第11章 全球人工智慧病理解決方案市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第12章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第13章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第14章：公司簡介

  • Paige AI
  • PathAI
  • Ibex Medical Analytics
  • Proscia
  • Visiopharm
  • Inspirata
  • Roche Holding AG
  • Philips Healthcare
  • Leica Biosystems
  • Hamamatsu Photonics
  • Aiforia Technologies
  • Nucleai
  • Huron Digital Pathology
  • Tempus AI
  • Mindpeak
Product Code: SMRC36784

According to Stratistics MRC, the Global AI-Based Pathology Solutions Market is accounted for $1.8 billion in 2026 and is expected to reach $7.2 billion by 2034, growing at a CAGR of 18.9% during the forecast period. AI-Based Pathology Solutions encompass software and hardware platforms that leverage artificial intelligence, machine learning, and computer vision algorithms to enhance the accuracy, efficiency, and scalability of pathological analysis. These solutions digitize glass tissue slides into high-resolution whole slide images and apply deep learning models to detect, quantify, and classify cellular morphologies, biomarkers, and tissue patterns relevant to cancer diagnosis, prognosis, and treatment response assessment.

Market Dynamics:

Driver:

Critical pathologist workforce shortage and rising global cancer diagnosis volume

A severe and widening shortage of trained pathologists, particularly across emerging markets and rural healthcare environments, combined with exponentially growing cancer diagnosis volumes, is creating an urgent demand for AI-augmented pathology workflows. Traditional manual slide review is time-consuming and subject to inter-observer variability, creating diagnostic backlogs that delay treatment initiation for cancer patients. AI-based image analysis platforms offer a scalable solution by automating routine screening tasks, prioritizing high-risk cases for expedited pathologist review, and providing quantitative biomarker assessments that reduce subjective interpretation differences. This operational imperative is the primary catalyst for rapid market adoption.

Restraint:

Limited reimbursement frameworks for digital and AI-assisted pathology services

Despite the clinical and operational benefits demonstrated by AI-based pathology platforms, reimbursement structures for digital pathology and AI-assisted diagnostic services remain inadequately defined across most healthcare systems. The absence of specific billing codes for AI-augmented pathology reads in major markets including the United States and Europe creates financial disincentives for laboratories contemplating the significant capital investment required for whole slide imaging infrastructure and AI software integration. Without clear revenue recognition pathways, laboratory directors face difficulty building business cases that justify transition away from established conventional microscopy workflows, constraining market adoption velocity.

Opportunity:

Expansion of companion diagnostics and biomarker quantification applications

The proliferation of immunotherapy and targeted oncology treatments dependent on companion diagnostic testing is creating a substantial growth opportunity for AI-based pathology platforms capable of automating biomarker quantification from tissue sections. AI algorithms can perform consistent, high-throughput quantification of PD-L1 expression, HER2 scoring, tumor-infiltrating lymphocyte density, and other therapeutically predictive biomarkers with reproducibility that surpasses manual assessment. As the number of approved cancer therapies with companion diagnostic requirements grows, demand for AI-powered pathology tools that can deliver standardized, scalable, and auditable biomarker analysis is set to expand significantly across pharmaceutical development and clinical oncology settings.

Threat:

Validation challenges and regulatory uncertainty for AI diagnostic algorithms

AI pathology algorithms require rigorous clinical validation across diverse patient populations, tissue types, and staining protocols before they can be reliably deployed in clinical practice. Demonstrating generalizability across laboratory environments with varying pre-analytical variables presents significant technical and regulatory challenges. Regulatory agencies including the FDA and EMA are developing frameworks for AI-based medical device software, but the pace of regulatory guidance development has not kept pace with the speed of algorithmic innovation, creating approval uncertainty for manufacturers. Furthermore, the risk of systematic diagnostic errors arising from algorithmic biases in training data could expose developers to significant liability and undermine clinical confidence in AI pathology tools.

Covid-19 Impact:

The COVID-19 pandemic disrupted pathology laboratory operations through staff shortages, prioritization of infectious disease testing, and delays in non-urgent cancer screening programs, temporarily suppressing demand for AI pathology solutions. However, the pandemic highlighted the vulnerability of pathology workflows dependent on physical presence and manual processes, reinforcing the case for digital transformation. Remote pathology review, enabled by whole slide imaging and AI-assisted triage, emerged as a resilient model during lockdowns, accelerating institutional interest in permanent digital pathology infrastructure investments. Post-pandemic recovery of cancer screening volumes is sustaining strong demand for AI tools that can address accumulated diagnostic backlogs efficiently.

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. Image analysis software, workflow management platforms, and diagnostic support tools constitute the highest-value components of the AI pathology ecosystem, capturing premium subscription and licensing revenues from pathology laboratories and pharmaceutical research organizations. Continuous algorithmic improvement, expanding tissue type coverage, and integration with laboratory information systems are sustaining software demand. The transition toward SaaS delivery models is broadening software accessibility, enabling smaller laboratories to adopt AI pathology capabilities without prohibitive infrastructure investment.

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

Over the forecast period, the Deep Learning segment is predicted to witness the highest growth rate. Deep learning convolutional neural networks have demonstrated superior performance in detecting subtle histological patterns associated with cancer, outperforming both conventional machine learning approaches and, in specific diagnostic tasks, expert pathologists. The growing availability of large annotated digital pathology datasets for model training, combined with advances in computational hardware enabling efficient neural network inference, is accelerating deep learning application development across tumor classification, grading, and biomarker quantification tasks in clinical and research settings.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share. The region benefits from a well-established digital pathology infrastructure, high cancer incidence rates creating sustained diagnostic demand, and strong pharmaceutical industry investment in computational pathology for drug development applications. Leading AI pathology companies are predominantly headquartered in the United States, ensuring early domestic market penetration. Favorable FDA regulatory engagement with AI diagnostic software, combined with growing laboratory accreditation requirements emphasizing quality and reproducibility, supports continued North American market leadership.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. Rapidly expanding cancer incidence across the region, combined with a critical shortage of pathologists in countries such as India and China, is driving urgent demand for AI-augmented diagnostic tools. Government-backed digital health modernization initiatives and growing investment by hospital networks in whole slide imaging infrastructure are creating a receptive market environment. South Korea and Japan, with their advanced healthcare technology adoption rates, are also contributing significantly to regional AI pathology market growth, particularly in research and pharmaceutical applications.

Key players in the market

Some of the key players in Global AI-Based Pathology Solutions Market include Paige AI, PathAI, Ibex Medical Analytics, Proscia, Visiopharm, Inspirata, Roche Holding AG, Philips Healthcare, Leica Biosystems, Hamamatsu Photonics, Aiforia Technologies, Nucleai, Huron Digital Pathology, Tempus AI, and Mindpeak.

Key Developments:

In January 2026, Paige AI announced FDA clearance for its expanded Paige Prostate AI system, now capable of detecting and grading prostate cancer across a wider range of Gleason patterns with enhanced specificity. The updated algorithm was validated on a diverse multi-institutional dataset, addressing a key regulatory requirement for generalizability. The clearance enables commercial deployment of the enhanced system across pathology laboratories and urology centers in the United States.

In February 2026, Roche Holding AG announced the integration of its NAVIFY Digital Pathology platform with PathAI's computational pathology algorithms, creating a combined solution for automated PD-L1 scoring and tumor microenvironment characterization. The integrated platform is designed to support pharmaceutical companies conducting immuno-oncology clinical trials requiring consistent, high-throughput biomarker analysis from archival and fresh tissue samples across global investigational sites.

Components Covered:

  • Software
  • Hardware
  • Services

Deployment Modes Covered:

  • On-premise
  • Cloud-based
  • Hybrid Deployment

Technologies Covered:

  • Machine Learning (ML)
  • Deep Learning
  • Computer Vision
  • Natural Language Processing (NLP)
  • Predictive Analytics

Pathology Types Covered:

  • Anatomical Pathology
  • Clinical Pathology
  • Molecular Pathology
  • Digital Pathology

Therapeutic Areas Covered:

  • Oncology
  • Neurology
  • Cardiovascular Diseases
  • Infectious Diseases
  • Dermatology
  • Gastrointestinal Disorders
  • Pulmonary Diseases
  • Other Therapeutic Areas

End Users Covered:

  • Hospitals
  • Diagnostic Laboratories
  • Academic & Research Institutes
  • Pharmaceutical & Biotechnology Companies
  • Contract Research Organizations (CROs)

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of 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 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • 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

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI-Based Pathology Solutions Market, By Component

  • 5.1 Software
    • 5.1.1 Image Analysis Software
    • 5.1.2 Workflow Management Software
    • 5.1.3 Diagnostic Support Software
    • 5.1.4 Predictive Analytics Software
  • 5.2 Hardware
    • 5.2.1 Whole Slide Imaging Scanners
    • 5.2.2 Servers & Storage Systems
    • 5.2.3 High-performance Computing Infrastructure
  • 5.3 Services
    • 5.3.1 Consulting Services
    • 5.3.2 Integration & Deployment Services
    • 5.3.3 Maintenance & Support Services
    • 5.3.4 Training Services

6 Global AI-Based Pathology Solutions Market, By Deployment Mode

  • 6.1 On-premise
  • 6.2 Cloud-based
  • 6.3 Hybrid Deployment

7 Global AI-Based Pathology Solutions Market, By Technology

  • 7.1 Machine Learning (ML)
  • 7.2 Deep Learning
  • 7.3 Computer Vision
  • 7.4 Natural Language Processing (NLP)
  • 7.5 Predictive Analytics

8 Global AI-Based Pathology Solutions Market, By Pathology Type

  • 8.1 Anatomical Pathology
  • 8.2 Clinical Pathology
  • 8.3 Molecular Pathology
  • 8.4 Digital Pathology

9 Global AI-Based Pathology Solutions Market, By Therapeutic Area

  • 9.1 Oncology
  • 9.2 Neurology
  • 9.3 Cardiovascular Diseases
  • 9.4 Infectious Diseases
  • 9.5 Dermatology
  • 9.6 Gastrointestinal Disorders
  • 9.7 Pulmonary Diseases
  • 9.8 Other Therapeutic Areas

10 Global AI-Based Pathology Solutions Market, By End User

  • 10.1 Hospitals
  • 10.2 Diagnostic Laboratories
  • 10.3 Academic & Research Institutes
  • 10.4 Pharmaceutical & Biotechnology Companies
  • 10.5 Contract Research Organizations (CROs)

11 Global AI-Based Pathology Solutions Market, By Geography

  • 11.1 North America
    • 11.1.1 United States
    • 11.1.2 Canada
    • 11.1.3 Mexico
  • 11.2 Europe
    • 11.2.1 United Kingdom
    • 11.2.2 Germany
    • 11.2.3 France
    • 11.2.4 Italy
    • 11.2.5 Spain
    • 11.2.6 Netherlands
    • 11.2.7 Belgium
    • 11.2.8 Sweden
    • 11.2.9 Switzerland
    • 11.2.10 Poland
    • 11.2.11 Rest of Europe
  • 11.3 Asia Pacific
    • 11.3.1 China
    • 11.3.2 Japan
    • 11.3.3 India
    • 11.3.4 South Korea
    • 11.3.5 Australia
    • 11.3.6 Indonesia
    • 11.3.7 Thailand
    • 11.3.8 Malaysia
    • 11.3.9 Singapore
    • 11.3.10 Vietnam
    • 11.3.11 Rest of Asia Pacific
  • 11.4 South America
    • 11.4.1 Brazil
    • 11.4.2 Argentina
    • 11.4.3 Colombia
    • 11.4.4 Chile
    • 11.4.5 Peru
    • 11.4.6 Rest of South America
  • 11.5 Rest of the World (RoW)
    • 11.5.1 Middle East
      • 11.5.1.1 Saudi Arabia
      • 11.5.1.2 United Arab Emirates
      • 11.5.1.3 Qatar
      • 11.5.1.4 Israel
      • 11.5.1.5 Rest of Middle East
    • 11.5.2 Africa
      • 11.5.2.1 South Africa
      • 11.5.2.2 Egypt
      • 11.5.2.3 Morocco
      • 11.5.2.4 Rest of Africa

12 Strategic Market Intelligence

  • 12.1 Industry Value Network and Supply Chain Assessment
  • 12.2 White-Space and Opportunity Mapping
  • 12.3 Product Evolution and Market Life Cycle Analysis
  • 12.4 Channel, Distributor, and Go-to-Market Assessment

13 Industry Developments and Strategic Initiatives

  • 13.1 Mergers and Acquisitions
  • 13.2 Partnerships, Alliances, and Joint Ventures
  • 13.3 New Product Launches and Certifications
  • 13.4 Capacity Expansion and Investments
  • 13.5 Other Strategic Initiatives

14 Company Profiles

  • 14.1 Paige AI
  • 14.2 PathAI
  • 14.3 Ibex Medical Analytics
  • 14.4 Proscia
  • 14.5 Visiopharm
  • 14.6 Inspirata
  • 14.7 Roche Holding AG
  • 14.8 Philips Healthcare
  • 14.9 Leica Biosystems
  • 14.10 Hamamatsu Photonics
  • 14.11 Aiforia Technologies
  • 14.12 Nucleai
  • 14.13 Huron Digital Pathology
  • 14.14 Tempus AI
  • 14.15 Mindpeak

List of Tables

  • Table 1 Global AI-Based Pathology Solutions Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI-Based Pathology Solutions Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI-Based Pathology Solutions Market Outlook, By Software (2023-2034) ($MN)
  • Table 4 Global AI-Based Pathology Solutions Market Outlook, By Image Analysis Software (2023-2034) ($MN)
  • Table 5 Global AI-Based Pathology Solutions Market Outlook, By Workflow Management Software (2023-2034) ($MN)
  • Table 6 Global AI-Based Pathology Solutions Market Outlook, By Diagnostic Support Software (2023-2034) ($MN)
  • Table 7 Global AI-Based Pathology Solutions Market Outlook, By Predictive Analytics Software (2023-2034) ($MN)
  • Table 8 Global AI-Based Pathology Solutions Market Outlook, By Hardware (2023-2034) ($MN)
  • Table 9 Global AI-Based Pathology Solutions Market Outlook, By Whole Slide Imaging Scanners (2023-2034) ($MN)
  • Table 10 Global AI-Based Pathology Solutions Market Outlook, By Servers & Storage Systems (2023-2034) ($MN)
  • Table 11 Global AI-Based Pathology Solutions Market Outlook, By High-performance Computing Infrastructure (2023-2034) ($MN)
  • Table 12 Global AI-Based Pathology Solutions Market Outlook, By Services (2023-2034) ($MN)
  • Table 13 Global AI-Based Pathology Solutions Market Outlook, By Consulting Services (2023-2034) ($MN)
  • Table 14 Global AI-Based Pathology Solutions Market Outlook, By Integration & Deployment Services (2023-2034) ($MN)
  • Table 15 Global AI-Based Pathology Solutions Market Outlook, By Maintenance & Support Services (2023-2034) ($MN)
  • Table 16 Global AI-Based Pathology Solutions Market Outlook, By Training Services (2023-2034) ($MN)
  • Table 17 Global AI-Based Pathology Solutions Market Outlook, By Deployment Mode (2023-2034) ($MN)
  • Table 18 Global AI-Based Pathology Solutions Market Outlook, By On-premise (2023-2034) ($MN)
  • Table 19 Global AI-Based Pathology Solutions Market Outlook, By Cloud-based (2023-2034) ($MN)
  • Table 20 Global AI-Based Pathology Solutions Market Outlook, By Hybrid Deployment (2023-2034) ($MN)
  • Table 21 Global AI-Based Pathology Solutions Market Outlook, By Technology (2023-2034) ($MN)
  • Table 22 Global AI-Based Pathology Solutions Market Outlook, By Machine Learning (ML) (2023-2034) ($MN)
  • Table 23 Global AI-Based Pathology Solutions Market Outlook, By Deep Learning (2023-2034) ($MN)
  • Table 24 Global AI-Based Pathology Solutions Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 25 Global AI-Based Pathology Solutions Market Outlook, By Natural Language Processing (NLP) (2023-2034) ($MN)
  • Table 26 Global AI-Based Pathology Solutions Market Outlook, By Predictive Analytics (2023-2034) ($MN)
  • Table 27 Global AI-Based Pathology Solutions Market Outlook, By Pathology Type (2023-2034) ($MN)
  • Table 28 Global AI-Based Pathology Solutions Market Outlook, By Anatomical Pathology (2023-2034) ($MN)
  • Table 29 Global AI-Based Pathology Solutions Market Outlook, By Clinical Pathology (2023-2034) ($MN)
  • Table 30 Global AI-Based Pathology Solutions Market Outlook, By Molecular Pathology (2023-2034) ($MN)
  • Table 31 Global AI-Based Pathology Solutions Market Outlook, By Digital Pathology (2023-2034) ($MN)
  • Table 32 Global AI-Based Pathology Solutions Market Outlook, By Therapeutic Area (2023-2034) ($MN)
  • Table 33 Global AI-Based Pathology Solutions Market Outlook, By Oncology (2023-2034) ($MN)
  • Table 34 Global AI-Based Pathology Solutions Market Outlook, By Neurology (2023-2034) ($MN)
  • Table 35 Global AI-Based Pathology Solutions Market Outlook, By Cardiovascular Diseases (2023-2034) ($MN)
  • Table 36 Global AI-Based Pathology Solutions Market Outlook, By Infectious Diseases (2023-2034) ($MN)
  • Table 37 Global AI-Based Pathology Solutions Market Outlook, By Dermatology (2023-2034) ($MN)
  • Table 38 Global AI-Based Pathology Solutions Market Outlook, By Gastrointestinal Disorders (2023-2034) ($MN)
  • Table 39 Global AI-Based Pathology Solutions Market Outlook, By Pulmonary Diseases (2023-2034) ($MN)
  • Table 40 Global AI-Based Pathology Solutions Market Outlook, By Other Therapeutic Areas (2023-2034) ($MN)
  • Table 41 Global AI-Based Pathology Solutions Market Outlook, By End User (2023-2034) ($MN)
  • Table 42 Global AI-Based Pathology Solutions Market Outlook, By Hospitals (2023-2034) ($MN)
  • Table 43 Global AI-Based Pathology Solutions Market Outlook, By Diagnostic Laboratories (2023-2034) ($MN)
  • Table 44 Global AI-Based Pathology Solutions Market Outlook, By Academic & Research Institutes (2023-2034) ($MN)
  • Table 45 Global AI-Based Pathology Solutions Market Outlook, By Pharmaceutical & Biotechnology Companies (2023-2034) ($MN)
  • Table 46 Global AI-Based Pathology Solutions Market Outlook, By Contract Research Organizations (CROs) (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.