
North America Computational Pathology Market Size, Share & Trends Analysis Report By Component (Software and Services), By Application, By End-use, By Technology, By Country and Growth Forecast, 2025 - 2032
Description
The North America Computational Pathology Market would witness market growth of 7.4% CAGR during the forecast period (2025-2032).
The US market dominated the North America Computational Pathology Market by Country in 2024, and would continue to be a dominant market till 2032; thereby, achieving a market value of $321.3 million by 2032. The Canada market is experiencing a CAGR of 9.6% during (2025 - 2032). Additionally, The Mexico market would exhibit a CAGR of 8.6% during (2025 - 2032).
This market is rapidly emerging as a transformative force in the medical and healthcare sectors, potentially revolutionizing how pathologists diagnose diseases and provide patient care. It integrates advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), and data analytics with traditional pathology practices to analyze medical data more accurately, efficiently, and in a way that enhances diagnostic capabilities.
The market is growing rapidly, driven by an increasing demand for precise diagnostics, personalized medicine, and more efficient workflows in laboratories and hospitals. Computational pathology, which uses computational algorithms to analyze pathology data, has many applications in clinical diagnostics, research, and personalized medicine. One key application is the automated analysis of digital pathology slides.
Canada’s government has pledged $198.6 billion over ten years to strengthen healthcare services, including $46.2 billion in new funding for provinces and territories. This investment aims to modernize healthcare infrastructure, reduce diagnostic delays, and enhance access to advanced technologies. These pathology stands to benefit significantly from this push, particularly in cancer care, pathology labs, and Indigenous health initiatives. As Canada focuses on improving early diagnosis and equitable healthcare delivery, the demand for scalable, AI-enabled diagnostic solutions like computational pathology is expected to rise considerably. In Mexico, cancer has become the third leading cause of death, with more than 195,000 new cases reported in 2020 alone. Breast, prostate, thyroid, colon, and cervical cancers are among the most prevalent, creating an urgent need for accurate and timely diagnosis. Computational pathology, with its ability to provide high-resolution digital imaging and AI-assisted tissue analysis, offers a powerful solution to Mexico’s growing cancer burden. In summary, the increasing healthcare investments in Canada, the rising cancer burden in Mexico, and the high per capita U.S. spending collectively drive substantial growth in the market across North America.
Based on Component, the market is segmented into Software and Services. Based on Application, the market is segmented into Disease Diagnosis, Drug Discovery & Development, and Academic Research. Based on End-use, the market is segmented into Hospitals and Diagnostic Labs, Biotechnology & Pharmaceutical Companies, Academic and Research Institutes, and Other End-use. Based on Technology, the market is segmented into Machine Learning (ML), (Deep Learning and Other Machine Learning (ML)), Computer Vision, Natural Language Processing (NLP) Models, and Other Technology. Based on countries, the market is segmented into U.S., Mexico, Canada, and Rest of North America.
List of Key Companies Profiled
By Component
The US market dominated the North America Computational Pathology Market by Country in 2024, and would continue to be a dominant market till 2032; thereby, achieving a market value of $321.3 million by 2032. The Canada market is experiencing a CAGR of 9.6% during (2025 - 2032). Additionally, The Mexico market would exhibit a CAGR of 8.6% during (2025 - 2032).
This market is rapidly emerging as a transformative force in the medical and healthcare sectors, potentially revolutionizing how pathologists diagnose diseases and provide patient care. It integrates advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), and data analytics with traditional pathology practices to analyze medical data more accurately, efficiently, and in a way that enhances diagnostic capabilities.
The market is growing rapidly, driven by an increasing demand for precise diagnostics, personalized medicine, and more efficient workflows in laboratories and hospitals. Computational pathology, which uses computational algorithms to analyze pathology data, has many applications in clinical diagnostics, research, and personalized medicine. One key application is the automated analysis of digital pathology slides.
Canada’s government has pledged $198.6 billion over ten years to strengthen healthcare services, including $46.2 billion in new funding for provinces and territories. This investment aims to modernize healthcare infrastructure, reduce diagnostic delays, and enhance access to advanced technologies. These pathology stands to benefit significantly from this push, particularly in cancer care, pathology labs, and Indigenous health initiatives. As Canada focuses on improving early diagnosis and equitable healthcare delivery, the demand for scalable, AI-enabled diagnostic solutions like computational pathology is expected to rise considerably. In Mexico, cancer has become the third leading cause of death, with more than 195,000 new cases reported in 2020 alone. Breast, prostate, thyroid, colon, and cervical cancers are among the most prevalent, creating an urgent need for accurate and timely diagnosis. Computational pathology, with its ability to provide high-resolution digital imaging and AI-assisted tissue analysis, offers a powerful solution to Mexico’s growing cancer burden. In summary, the increasing healthcare investments in Canada, the rising cancer burden in Mexico, and the high per capita U.S. spending collectively drive substantial growth in the market across North America.
Based on Component, the market is segmented into Software and Services. Based on Application, the market is segmented into Disease Diagnosis, Drug Discovery & Development, and Academic Research. Based on End-use, the market is segmented into Hospitals and Diagnostic Labs, Biotechnology & Pharmaceutical Companies, Academic and Research Institutes, and Other End-use. Based on Technology, the market is segmented into Machine Learning (ML), (Deep Learning and Other Machine Learning (ML)), Computer Vision, Natural Language Processing (NLP) Models, and Other Technology. Based on countries, the market is segmented into U.S., Mexico, Canada, and Rest of North America.
List of Key Companies Profiled
- Koninklijke Philips N.V.
- F. Hoffmann-La Roche Ltd.
- PathAI, Inc.
- Hamamatsu Photonics K.K.
- Olympus Corporation
- Visiopharm A/S
- Mikroscan Technologies, Inc.
- MindPeak GmbH
- Indica Labs, LLC
- Nucleai, Inc. (Nucleai)
By Component
- Software
- Services
- Disease Diagnosis
- Drug Discovery & Development
- Academic Research
- Hospitals and Diagnostic Labs
- Biotechnology & Pharmaceutical Companies
- Academic and Research Institutes
- Other End-use
- Machine Learning (ML)
- Deep Learning
- Other Machine Learning (ML)
- Computer Vision
- Natural Language Processing (NLP) Models
- Other Technology
- US
- Canada
- Mexico
- Rest of North America
Table of Contents
132 Pages
- Chapter 1. Market Scope & Methodology
- 1.1 Market Definition
- 1.2 Objectives
- 1.3 Market Scope
- 1.4 Segmentation
- 1.4.1 North America Computational Pathology Market, by Component
- 1.4.2 North America Computational Pathology Market, by Application
- 1.4.3 North America Computational Pathology Market, by End-use
- 1.4.4 North America Computational Pathology Market, by Technology
- 1.4.5 North America Computational Pathology Market, by Country
- 1.5 Methodology for the research
- Chapter 2. Market at a Glance
- 2.1 Key Highlights
- Chapter 3. Market Overview
- 3.1 Introduction
- 3.1.1 Overview
- 3.1.1.1 Market Composition and Scenario
- 3.2 Key Factors Impacting the Market
- 3.2.1 Market Drivers
- 3.2.2 Market Restraints
- 3.2.3 Market Opportunities
- 3.2.4 Market Challenges
- Chapter 4. Competition Analysis - Global
- 4.1 KBV Cardinal Matrix
- 4.2 Recent Industry Wide Strategic Developments
- 4.2.1 Partnerships, Collaborations and Agreements
- 4.2.2 Product Launches and Product Expansions
- 4.3 Market Share Analysis, 2024
- 4.4 Top Winning Strategies
- 4.4.1 Key Leading Strategies: Percentage Distribution (2021-2025)
- 4.4.2 Key Strategic Move: (Partnerships, Collaborations & Agreements : 2022, Mar – 2025, Feb) Leading Players
- 4.5 Porter Five Forces Analysis
- Chapter 5. North America Computational Pathology Market by Component
- 5.1 North America Software Market by Region
- 5.2 North America Services Market by Region
- Chapter 6. North America Computational Pathology Market by Application
- 6.1 North America Disease Diagnosis Market by Country
- 6.2 North America Drug Discovery & Development Market by Country
- 6.3 North America Academic Research Market by Country
- Chapter 7. North America Computational Pathology Market by End-use
- 7.1 North America Hospitals and Diagnostic Labs Market by Country
- 7.2 North America Biotechnology & Pharmaceutical Companies Market by Country
- 7.3 North America Academic and Research Institutes Market by Country
- 7.4 North America Other End-use Market by Country
- Chapter 8. North America Computational Pathology Market by Technology
- 8.1 North America Machine Learning (ML) Market by Country
- 8.2 North America Computational Pathology Market by Machine Learning (ML) Type
- 8.2.1 North America Deep Learning Market by Country
- 8.2.2 North America Other Machine Learning (ML) Market by Country
- 8.3 North America Computer Vision Market by Country
- 8.4 North America Natural Language Processing (NLP) Models Market by Country
- 8.5 North America Other Technology Market by Country
- Chapter 9. North America Computational Pathology Market by Country
- 9.1 US Computational Pathology Market
- 9.1.1 US Computational Pathology Market by Component
- 9.1.2 US Computational Pathology Market by Application
- 9.1.3 US Computational Pathology Market by End-use
- 9.1.4 US Computational Pathology Market by Technology
- 9.1.4.1 US Computational Pathology Market by Machine Learning (ML) Type
- 9.2 Canada Computational Pathology Market
- 9.2.1 Canada Computational Pathology Market by Component
- 9.2.2 Canada Computational Pathology Market by Application
- 9.2.3 Canada Computational Pathology Market by End-use
- 9.2.4 Canada Computational Pathology Market by Technology
- 9.2.4.1 Canada Computational Pathology Market by Machine Learning (ML) Type
- 9.3 Mexico Computational Pathology Market
- 9.3.1 Mexico Computational Pathology Market by Component
- 9.3.2 Mexico Computational Pathology Market by Application
- 9.3.3 Mexico Computational Pathology Market by End-use
- 9.3.4 Mexico Computational Pathology Market by Technology
- 9.3.4.1 Mexico Computational Pathology Market by Machine Learning (ML) Type
- 9.4 Rest of North America Computational Pathology Market
- 9.4.1 Rest of North America Computational Pathology Market by Component
- 9.4.2 Rest of North America Computational Pathology Market by Application
- 9.4.3 Rest of North America Computational Pathology Market by End-use
- 9.4.4 Rest of North America Computational Pathology Market by Technology
- 9.4.4.1 Rest of North America Computational Pathology Market by Machine Learning (ML) Type
- Chapter 10. Company Profiles
- 10.1 Koninklijke Philips N.V.
- 10.1.1 Company Overview
- 10.1.2 Financial Analysis
- 10.1.3 Segmental and Regional Analysis
- 10.1.4 Research & Development Expense
- 10.1.5 Recent strategies and developments:
- 10.1.5.1 Partnerships, Collaborations, and Agreements:
- 10.1.6 SWOT Analysis
- 10.2 F. Hoffmann-La Roche Ltd.
- 10.2.1 Company Overview
- 10.2.2 Financial Analysis
- 10.2.3 Segmental and Regional Analysis
- 10.2.4 Research & Development Expense
- 10.2.5 Recent strategies and developments:
- 10.2.5.1 Partnerships, Collaborations, and Agreements:
- 10.2.5.2 Product Launches and Product Expansions:
- 10.2.6 SWOT Analysis
- 10.3 PathAI, Inc.
- 10.3.1 Company Overview
- 10.3.2 Recent strategies and developments:
- 10.3.2.1 Partnerships, Collaborations, and Agreements:
- 10.3.2.2 Product Launches and Product Expansions:
- 10.3.3 SWOT Analysis
- 10.4 Hamamatsu Photonics K.K.
- 10.4.1 Company Overview
- 10.4.2 Financial Analysis
- 10.4.3 Segmental Analysis
- 10.4.4 Research & Development Expense
- 10.4.5 SWOT Analysis
- 10.5 Olympus Corporation
- 10.5.1 Company Overview
- 10.5.2 Financial Analysis
- 10.5.3 Segmental and Regional Analysis
- 10.5.4 SWOT Analysis
- 10.6 Visiopharm A/S
- 10.6.1 Company Overview
- 10.6.2 Recent strategies and developments:
- 10.6.2.1 Partnerships, Collaborations, and Agreements:
- 10.6.2.2 Product Launches and Product Expansions:
- 10.6.3 SWOT Analysis
- 10.7 Mikroscan Technologies, Inc.
- 10.7.1 Company Overview
- 10.8 MindPeak GmbH
- 10.8.1 Company Overview
- 10.8.2 Recent strategies and developments:
- 10.8.2.1 Partnerships, Collaborations, and Agreements:
- 10.9 Indica Labs, Inc.
- 10.9.1 Company Overview
- 10.9.2 Recent strategies and developments:
- 10.9.2.1 Partnerships, Collaborations, and Agreements:
- 10.9.3 SWOT Analysis
- 10.10. Nucleai, Inc. (Nucleai)
- 10.10.1 Company Overview
- 10.10.2 Recent strategies and developments:
- 10.10.2.1 Partnerships, Collaborations, and Agreements:
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