시장보고서
상품코드
1719550

계산 병리학 시장 규모, 점유율, 동향 분석 보고서 : 컴포넌트별, 용도별, 최종 용도별, 기술별, 지역별, 전망 및 예측(2025-2032년)

Global Computational Pathology Market Size, Share & Trends Analysis Report By Component (Software and Services), By Application, By End-use, By Technology, By Regional Outlook and Forecast, 2025 - 2032

발행일: | 리서치사: KBV Research | 페이지 정보: 영문 352 Pages | 배송안내 : 즉시배송

    
    
    



※ 본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문 목차를 참고해주시기 바랍니다.

세계의 계산 병리학 시장 규모는 2032년까지 12억 달러로 성장할 것으로 예측되고, 예측 기간 동안 7.9%의 연평균 성장률(CAGR)로 시장 성장할 전망입니다.

KBV Cardinal matrix - 계산 병리학 시장 경쟁 분석

KBV Cardinal matrix에 제시된 분석에 따라 F. Hoffmann-La Roche Ltd.는 계산 병리학 시장의 선구자입니다. Hoffmann-La Roche Ltd.는 Bristol Myers Squibb와 협력했습니다. 이 협력은 AI 기반 디지털 진단의 개발과 도입을 가속화하여 보다 정확하고 효율적인 병리학 인사이트를 통해 임상 의사 결정과 환자 치료를 개선하는 것을 목표로 합니다.

시장 성장 요인

임상 및 연구 환경에서 디지털 병리학 솔루션의 채택이 증가하는 것이 시장의 주요 동인입니다. 전통적인 병리학은 오랫동안 현미경으로 유리 슬라이드를 수동으로 검사하는 방식에 의존해왔는데, 이 과정은 시간이 많이 걸리고 인적 오류가 발생할 수 있으며 확장성이 제한적이었습니다. 병리 슬라이드를 디지털화하는 방향으로 전환하면서 고해상도 이미지 캡처가 가능해져 컴퓨터 기술을 적용하여 훨씬 더 빠르고 정밀하며 일관성 있게 조직 샘플을 분석할 수 있게 되었습니다.

또한 선진국 및 신흥 시장에서 의료 IT 인프라가 지속적으로 확장되고 있는 것도 병리학의 성장에 크게 기여하고 있습니다. 전자 의료 기록(EHR), 의료 영상 보관 및 통신 시스템(PACS), 실험실 정보 관리 시스템(LIMS) 및 기타 디지털 도구의 통합은 계산 병리학이 번창할 수 있는 강력한 기반을 조성하고 있습니다. 따라서 전산 도구의 원활한 통합을 지원하는 의료 IT 인프라의 확장이 시장의 성장을 촉진하고 있습니다.

시장 성장 억제요인

그러나 이 병리학의 광범위한 채택에 가장 큰 제약 요인 중 하나는 필요한 인프라 구현과 관련된 높은 초기 비용입니다. 이러한 비용에는 전체 슬라이드 이미징 스캐너, 고성능 컴퓨팅(HPC) 시스템, 데이터 스토리지 서버, AI 기반 분석 소프트웨어, 기존 의료 정보 시스템과 연결하기 위한 통합 도구 구매가 포함됩니다. 따라서 보다 저렴하고 확장 가능한 솔루션이 널리 보급되거나 저자원 환경을 지원하기 위한 자금 지원 프로그램이 도입될 때까지 높은 초기 비용은 시장 성장을 계속 저해할 것입니다.

컴포넌트 전망

시장은 컴포넌트별로 시장은 소프트웨어와 서비스로 구분됩니다. 서비스 부문은 2024년 시장에서 35%의 매출 점유율을 차지할 것으로 예상됩니다. 이는 이러한 병리 시스템의 구현과 최적화를 지원하는 컨설팅, 교육, 시스템 통합 및 유지보수 서비스에 대한 수요가 증가했기 때문입니다. 의료 서비스 제공업체가 디지털 병리학 솔루션을 점점 더 많이 채택함에 따라 전문가 지침과 지속적인 기술 지원에 대한 필요성이 커지면서 이 시장 부문의 서비스 수요가 증가하고 있습니다.

용도 전망

용도별로 보면 시장은 질병 진단, 신약 발견 및 개발, 학술 연구로 분류됩니다. 학술 연구 부문은 2024년 시장에서 24%의 매출 점유율을 기록했습니다. 생의학 연구에 대한 관심이 높아지고 학술 기관에서 컴퓨팅 도구의 역할이 확대되면서 이러한 성장을 뒷받침하고 있습니다.

최종 용도 전망

최종 용도에 따라 시장은 병원 및 진단 연구소, 생명공학 및 제약 회사, 학술 및 연구 기관 등으로 세분화됩니다. 생명 공학 및 제약 회사 부문은 2024년 시장에서 24%의 매출 점유율을 차지했습니다. 이는 신약 개발, 바이오마커 식별, 임상시험에서 계산 병리학의 사용이 증가했기 때문입니다. 이러한 기업들은 첨단 데이터 분석 및 이미징 기술을 사용하여 연구를 가속화하고 표적 치료법을 개발합니다. 높은 처리량과 재현 가능한 결과를 제공하는 계산 병리학의 능력은 제약 개발 프로세스의 혁신과 규제 준수를 지원합니다.

기술 전망

기술별로 보면, 머신러닝(ML), 자연어 처리(NLP) 모델, 컴퓨터 비전 등으로 나뉩니다. 자연어 처리(NLP) 모델 부문은 2024년 시장에서 17%의 매출 점유율을 차지했습니다. 이러한 성장은 병리 보고서 및 의료 기록과 같은 비정형 임상 데이터에서 의미 있는 인사이트를 추출하는 데 NLP의 사용이 증가했기 때문입니다. NLP 모델은 텍스트 데이터를 자동으로 해석하여 임상 정보를 진단 워크플로우와 연구에 더 잘 통합할 수 있게 해줍니다.

지역 전망

지역별로 볼 때 시장은 북미, 유럽, 아시아태평양 및 LAMEA 시장을 분석합니다. 유럽 부문은 2024년 시장에서 28%의 매출 점유율을 기록했습니다. 이 지역의 성장은 의료 디지털화 증가, 만성 질환의 유병률 증가, 정밀 의학에 대한 강조 증가에 의해 뒷받침됩니다. 또한 유럽 국가들은 병리학 및 진단과 관련된 연구 개발 활동과 디지털 의료 관행을 표준화하기 위한 노력에 막대한 투자를 하고 있으며, 이는 모두 대륙 전체에서 계산 병리학의 채택을 확대하는 데 기여하고 있습니다.

시장 경쟁과 특성

계산 병리학 시장은 스타트업, 중견 기업, 학계에서 분사한 기업 간의 경쟁이 심화되고 있습니다. 이러한 업체들은 틈새 용도, AI 기반 진단, 저렴한 소프트웨어 솔루션에 중점을 두고 있습니다. 혁신, 의료 서비스 제공업체와의 협업, 규제 적응력이 성장을 주도합니다. 거대 기업의 부재는 민첩한 기업이 시장 부문을 선점하고 미래 기술 개발에 영향을 미칠 수 있는 기회를 열어줍니다.

목차

제1장 시장 범위와 조사 방법

  • 시장의 정의
  • 목적
  • 시장 범위
  • 세분화
  • 조사 방법

제2장 시장 개관

  • 주요 하이라이트

제3장 시장 개요

  • 소개
    • 개요
      • 시장구성과 시나리오
  • 시장에 영향을 미치는 주요 요인
    • 시장 성장 촉진요인
    • 시장 성장 억제요인
    • 시장 기회
    • 시장 과제

제4장 경쟁 분석 - 세계

  • KBV Cardinal Matrix
  • 최근 업계 전체의 전략적 전개
    • 파트너쉽, 협업 및 계약
    • 제품 출시 및 제품 확대
  • 주요 성공 전략
    • 주요 전략
    • 주요 전략적 움직임
  • Porter's Five Forces 분석

제5장 세계의 계산 병리학 시장 : 컴포넌트별

  • 세계의 소프트웨어 시장 : 지역별
  • 세계의 서비스 시장 : 지역별

제6장 세계의 계산 병리학 시장 : 용도별

  • 세계의 질병 진단 시장 : 지역별
  • 세계의 신약 발견 및 개발 시장 : 지역별
  • 세계의 학술 연구 시장 : 지역별

제7장 세계의 계산 병리학 시장 : 최종 용도별

  • 세계의 병원 및 진단 연구소 시장 : 지역별
  • 세계의 생명공학 및 제약 회사 시장 : 지역별
  • 세계의 학술 및 연구 기관 시장 : 지역별
  • 세계의 기타 최종 용도 시장 : 지역별

제8장 세계의 계산 병리학 시장 : 기술별

  • 세계의 머신러닝(ML) 시장 : 지역별
  • 세계의 계산 병리학 시장 : 머신러닝(ML)유형별
  • 세계의 컴퓨터 비전 시장 : 지역별
  • 세계의 자연 언어 처리(NLP) 모델 시장 : 지역별
  • 세계의 기타 기술 시장 : 지역별

제9장 세계의 계산 병리학 시장 : 지역별

  • 북미
    • 북미 시장 : 국가별
      • 미국
      • 캐나다
      • 멕시코
      • 기타 북미
  • 유럽
    • 유럽 시장 : 국가별
      • 독일
      • 영국
      • 프랑스
      • 러시아
      • 스페인
      • 이탈리아
      • 기타 유럽
  • 아시아태평양
    • 아시아태평양 시장 : 국가별
      • 중국
      • 일본
      • 인도
      • 한국
      • 싱가포르
      • 말레이시아
      • 기타 아시아태평양
  • 라틴아메리카, 중동 및 아프리카
    • 라틴아메리카, 중동, 아프리카 시장 : 국가별
      • 브라질
      • 아르헨티나
      • 아랍에미리트(UAE)
      • 사우디아라비아
      • 남아프리카
      • 나이지리아
      • 기타 라틴아메리카, 중동 및 아프리카

제10장 기업 프로파일

  • Koninklijke Philips NV
  • F Hoffmann-La Roche Ltd.
  • PathAI, Inc
  • Hamamatsu Photonics KK
  • Olympus Corporation
  • Visiopharm A/S
  • Mikroscan Technologies, Inc
  • MindPeak GmbH
  • Indica Labs, Inc
  • Nucleai, Inc(Nucleai)
HBR 25.05.26

The Global Computational Pathology Market size is expected to reach $1.20 billion by 2032, rising at a market growth of 7.9% CAGR during the forecast period.

The North America segment recorded 39% revenue share in the market in 2024. The presence of advanced healthcare infrastructure, high adoption of digital technologies, and strong investments in AI and machine learning for medical applications drive this dominance. Additionally, favorable regulatory support and active research collaborations among academic institutions, hospitals, and tech companies have fuelled the rapid implementation of these pathology solutions across the region.

The major strategies followed by the market participants are Partnerships as the key developmental strategy to keep pace with the changing demands of end users. For instance, In February, 2025, PathAI, Inc. teamed up with Rede D'Or to introduce AI-driven pathology solutions in Brazil. This collaboration aims to enhance diagnostic accuracy and improve patient outcomes by integrating PathAI's advanced technologies into Rede D'Or's network, marking a significant step in modernizing healthcare across the region. Moreover, In January, 2025, Indica Labs, LLC teamed up with Leica Biosystems to develop a joint digital pathology platform. This collaboration aims to integrate Leica's imaging systems with Indica's AI-powered pathology software, enhancing diagnostic workflows and accelerating the adoption of digital pathology across clinical and research environments.

KBV Cardinal Matrix - Computational Pathology Market Competition Analysis

Based on the Analysis presented in the KBV Cardinal matrix; F. Hoffmann-La Roche Ltd. is the forerunner in the Computational Pathology Market. In March, 2022, F. Hoffmann-La Roche Ltd. teamed up with Bristol Myers Squibb to enhance personalized healthcare by advancing digital pathology solutions. This collaboration aims to accelerate the development and adoption of AI-based digital diagnostics, improving clinical decision-making and patient care through more precise and efficient pathology insights. Companies such as Olympus Corporation, Hamamatsu Photonics K.K., and PathAI, Inc. are some of the key innovators in Computational Pathology Market.

Market Growth Factors

The rising adoption of digital pathology solutions in clinical and research environments is a primary driver for the market. Traditional pathology has long relied on the manual examination of glass slides under a microscope, a process that can be time-consuming, subject to human error, and limited in scalability. The shift toward digitizing pathology slides allows for high-resolution image capture, enabling the application of computational techniques to analyze tissue samples with far greater speed, precision, and consistency. Thus, the growing adoption of digital pathology solutions in clinical and research settings drives the market's growth.

Additionally, The ongoing expansion of healthcare IT infrastructure across developed and emerging markets significantly contributes to the rise of this pathology. The integration of electronic health records (EHRs), picture archiving and communication systems (PACS), laboratory information management systems (LIMS), and other digital tools are creating a robust foundation for computational pathology to thrive. Thus, the expansion of healthcare IT infrastructure supporting seamless integration of computational tools is propelling the market's growth.

Market Restraining Factors

However, One of the most significant restraints to the widespread adoption of this pathology is the high upfront cost associated with implementing the necessary infrastructure. These costs include purchasing whole-slide imaging scanners, high-performance computing (HPC) systems, data storage servers, AI-powered analytical software, and integration tools to connect with existing health information systems. Therefore, the high initial cost will continue to hinder market growth until more affordable and scalable solutions become widely available or funding programs are introduced to support low-resource settings.

Component Outlook

Based on component, the market is characterized into software and services. The services segment procured 35% revenue share in the market in 2024. This is attributed to the rising demand for consulting, training, system integration, and maintenance services that support the implementation and optimization of these pathology systems. As healthcare providers increasingly adopt digital pathology solutions, the need for expert guidance and ongoing technical support has grown, fuelling the demand for services in this market segment.

Application Outlook

On the basis of application, the market is classified into disease diagnosis, drug discovery & development, and academic research. The academic research segment recorded 24% revenue share in the market in 2024. The rising focus on biomedical research and the expanding role of computational tools in academic institutions support this growth. Researchers increasingly utilize this pathology to study disease mechanisms, develop novel biomarkers, and train AI models for diagnostic applications.

End-use Outlook

Based on end-use, the market is segmented into hospitals & diagnostic labs, biotechnology & pharmaceutical companies, academic & research institutes, and others. The biotechnology & pharmaceutical companies segment acquired 24% revenue share in the market in 2024. This is due to the increasing use of computational pathology in drug discovery, biomarker identification, and clinical trials. These companies use advanced data analytics and imaging technologies to accelerate research and develop targeted therapies. The ability of computational pathology to provide high-throughput, reproducible results supports innovation and regulatory compliance in the pharmaceutical development process.

Technology Outlook

By technology, the market is divided into machine learning (ML), natural language processing (NLP) models, computer vision, and others. The natural language processing (NLP) models segment acquired 17% revenue share in the market in 2024. This growth is attributed to the increasing use of NLP in extracting meaningful insights from unstructured clinical data, such as pathology reports and medical records. NLP models enable the automatic interpretation of textual data, facilitating better integration of clinical information into diagnostic workflows and research.

Regional Outlook

Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The Europe segment witnessed 28% revenue share in the market in 2024. The growth in this region is supported by increasing healthcare digitization, the rising prevalence of chronic diseases, and the growing emphasis on precision medicine. European countries are also investing heavily in research and development activities related to pathology and diagnostics, along with initiatives to standardize digital health practices, all of which contribute to the expanding adoption of computational pathology across the continent.

Market Competition and Attributes

The Computational Pathology Market sees intensified competition among startups, mid-sized firms, and academic spin-offs. These players focus on niche applications, AI-driven diagnostics, and affordable software solutions. Innovation, collaborations with healthcare providers, and regulatory adaptability drive growth. The absence of giants opens opportunities for agile firms to capture market segments and influence future technological developments.

Recent Strategies Deployed in the Market

  • Sep-2024: Koninklijke Philips N.V. teamed up with IDEXX Laboratories to implement a global digital pathology solution, enhancing collaboration across its pathology network. This transformation enabled faster diagnoses, improved workflow efficiency, and elevated diagnostic quality. Integrating Philips' technology supports IDEXX's mission to deliver timely, high-quality veterinary diagnostics worldwide through advanced digital tools.
  • May-2024: PathAI, Inc. unveiled Pluto, a cutting-edge foundation model designed to boost AI-powered pathology tools. Pluto enhances model performance, scalability, and precision in digital pathology. By integrating advanced AI, PathAI aims to accelerate innovation and improve outcomes in clinical diagnostics, research, and drug development through improved image analysis.
  • Feb-2024: PathAI, Inc. unveiled a new pathologist-focused feature on AISight, aimed at streamlining case reviews. These updates offer intelligent case prioritization and enable real-time collaboration across institutions, enhancing efficiency and diagnostic workflows for pathologists working in diverse healthcare settings.
  • Nov-2023: PathAI, Inc. unveiled ArtifactDetect on its AISight platform, a cutting-edge model designed to automate slide quality analysis in pathology labs. This innovation aims to improve diagnostic accuracy by detecting artifacts that compromise slide quality, enhancing lab efficiency, and enabling more reliable pathology workflows through artificial intelligence.
  • Oct-2023: Visiopharm A/S teamed up with NPIC to improve standardization in H&E staining using AI-driven digital pathology. This collaboration aims to enhance diagnostic accuracy and consistency by developing objective quality control tools, marking a significant step toward more reliable and reproducible pathology results across laboratories.

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)

Global Computational Pathology Market Report Segmentation

By Component

  • Software
  • Services

By Application

  • Disease Diagnosis
  • Drug Discovery & Development
  • Academic Research

By End-use

  • Hospitals and Diagnostic Labs
  • Biotechnology & Pharmaceutical Companies
  • Academic and Research Institutes
  • Other End-use

By Technology

  • Machine Learning (ML)
    • Deep Learning
    • Other Machine Learning (ML)
  • Computer Vision
  • Natural Language Processing (NLP) Models
  • Other Technology

By Geography

  • North America
    • US
    • Canada
    • Mexico
    • Rest of North America
  • Europe
    • Germany
    • UK
    • France
    • Russia
    • Spain
    • Italy
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Singapore
    • Malaysia
    • Rest of Asia Pacific
  • LAMEA
    • Brazil
    • Argentina
    • UAE
    • Saudi Arabia
    • South Africa
    • Nigeria
  • Rest of LAMEA

Table of Contents

Chapter 1. Market Scope & Methodology

  • 1.1 Market Definition
  • 1.2 Objectives
  • 1.3 Market Scope
  • 1.4 Segmentation
    • 1.4.1 Global Computational Pathology Market, by Component
    • 1.4.2 Global Computational Pathology Market, by Application
    • 1.4.3 Global Computational Pathology Market, by End-use
    • 1.4.4 Global Computational Pathology Market, by Technology
    • 1.4.5 Global Computational Pathology Market, by Geography
  • 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 Top Winning Strategies
    • 4.3.1 Key Leading Strategies: Percentage Distribution (2021-2025)
    • 4.3.2 Key Strategic Move: (Partnerships, Collaborations & Agreements : 2022, Mar - 2025, Feb) Leading Players
  • 4.4 Porter Five Forces Analysis

Chapter 5. Global Computational Pathology Market by Component

  • 5.1 Global Software Market by Region
  • 5.2 Global Services Market by Region

Chapter 6. Global Computational Pathology Market by Application

  • 6.1 Global Disease Diagnosis Market by Region
  • 6.2 Global Drug Discovery & Development Market by Region
  • 6.3 Global Academic Research Market by Region

Chapter 7. Global Computational Pathology Market by End-use

  • 7.1 Global Hospitals and Diagnostic Labs Market by Region
  • 7.2 Global Biotechnology & Pharmaceutical Companies Market by Region
  • 7.3 Global Academic and Research Institutes Market by Region
  • 7.4 Global Other End-use Market by Region

Chapter 8. Global Computational Pathology Market by Technology

  • 8.1 Global Machine Learning (ML) Market by Region
  • 8.2 Global Computational Pathology Market by Machine Learning (ML) Type
    • 8.2.1 Global Deep Learning Market by Region
    • 8.2.2 Global Other Machine Learning (ML) Market by Region
  • 8.3 Global Computer Vision Market by Region
  • 8.4 Global Natural Language Processing (NLP) Models Market by Region
  • 8.5 Global Other Technology Market by Region

Chapter 9. Global Computational Pathology Market by Region

  • 9.1 North America Computational Pathology Market
    • 9.1.1 North America Computational Pathology Market by Component
      • 9.1.1.1 North America Software Market by Region
      • 9.1.1.2 North America Services Market by Region
    • 9.1.2 North America Computational Pathology Market by Application
      • 9.1.2.1 North America Disease Diagnosis Market by Country
      • 9.1.2.2 North America Drug Discovery & Development Market by Country
      • 9.1.2.3 North America Academic Research Market by Country
    • 9.1.3 North America Computational Pathology Market by End-use
      • 9.1.3.1 North America Hospitals and Diagnostic Labs Market by Country
      • 9.1.3.2 North America Biotechnology & Pharmaceutical Companies Market by Country
      • 9.1.3.3 North America Academic and Research Institutes Market by Country
      • 9.1.3.4 North America Other End-use Market by Country
    • 9.1.4 North America Computational Pathology Market by Technology
      • 9.1.4.1 North America Machine Learning (ML) Market by Country
      • 9.1.4.2 North America Computational Pathology Market by Machine Learning (ML) Type
        • 9.1.4.2.1 North America Deep Learning Market by Country
        • 9.1.4.2.2 North America Other Machine Learning (ML) Market by Country
      • 9.1.4.3 North America Computer Vision Market by Country
      • 9.1.4.4 North America Natural Language Processing (NLP) Models Market by Country
      • 9.1.4.5 North America Other Technology Market by Country
    • 9.1.5 North America Computational Pathology Market by Country
      • 9.1.5.1 US Computational Pathology Market
        • 9.1.5.1.1 US Computational Pathology Market by Component
        • 9.1.5.1.2 US Computational Pathology Market by Application
        • 9.1.5.1.3 US Computational Pathology Market by End-use
        • 9.1.5.1.4 US Computational Pathology Market by Technology
      • 9.1.5.2 Canada Computational Pathology Market
        • 9.1.5.2.1 Canada Computational Pathology Market by Component
        • 9.1.5.2.2 Canada Computational Pathology Market by Application
        • 9.1.5.2.3 Canada Computational Pathology Market by End-use
        • 9.1.5.2.4 Canada Computational Pathology Market by Technology
      • 9.1.5.3 Mexico Computational Pathology Market
        • 9.1.5.3.1 Mexico Computational Pathology Market by Component
        • 9.1.5.3.2 Mexico Computational Pathology Market by Application
        • 9.1.5.3.3 Mexico Computational Pathology Market by End-use
        • 9.1.5.3.4 Mexico Computational Pathology Market by Technology
      • 9.1.5.4 Rest of North America Computational Pathology Market
        • 9.1.5.4.1 Rest of North America Computational Pathology Market by Component
        • 9.1.5.4.2 Rest of North America Computational Pathology Market by Application
        • 9.1.5.4.3 Rest of North America Computational Pathology Market by End-use
        • 9.1.5.4.4 Rest of North America Computational Pathology Market by Technology
  • 9.2 Europe Computational Pathology Market
    • 9.2.1 Europe Computational Pathology Market by Component
      • 9.2.1.1 Europe Software Market by Country
      • 9.2.1.2 Europe Services Market by Country
    • 9.2.2 Europe Computational Pathology Market by Application
      • 9.2.2.1 Europe Disease Diagnosis Market by Country
      • 9.2.2.2 Europe Drug Discovery & Development Market by Country
      • 9.2.2.3 Europe Academic Research Market by Country
    • 9.2.3 Europe Computational Pathology Market by End-use
      • 9.2.3.1 Europe Hospitals and Diagnostic Labs Market by Country
      • 9.2.3.2 Europe Biotechnology & Pharmaceutical Companies Market by Country
      • 9.2.3.3 Europe Academic and Research Institutes Market by Country
      • 9.2.3.4 Europe Other End-use Market by Country
    • 9.2.4 Europe Computational Pathology Market by Technology
      • 9.2.4.1 Europe Machine Learning (ML) Market by Country
      • 9.2.4.2 Europe Computational Pathology Market by Machine Learning (ML) Type
        • 9.2.4.2.1 Europe Deep Learning Market by Country
        • 9.2.4.2.2 Europe Other Machine Learning (ML) Market by Country
      • 9.2.4.3 Europe Computer Vision Market by Country
      • 9.2.4.4 Europe Natural Language Processing (NLP) Models Market by Country
      • 9.2.4.5 Europe Other Technology Market by Country
    • 9.2.5 Europe Computational Pathology Market by Country
      • 9.2.5.1 Germany Computational Pathology Market
        • 9.2.5.1.1 Germany Computational Pathology Market by Component
        • 9.2.5.1.2 Germany Computational Pathology Market by Application
        • 9.2.5.1.3 Germany Computational Pathology Market by End-use
        • 9.2.5.1.4 Germany Computational Pathology Market by Technology
      • 9.2.5.2 UK Computational Pathology Market
        • 9.2.5.2.1 UK Computational Pathology Market by Component
        • 9.2.5.2.2 UK Computational Pathology Market by Application
        • 9.2.5.2.3 UK Computational Pathology Market by End-use
        • 9.2.5.2.4 UK Computational Pathology Market by Technology
      • 9.2.5.3 France Computational Pathology Market
        • 9.2.5.3.1 France Computational Pathology Market by Component
        • 9.2.5.3.2 France Computational Pathology Market by Application
        • 9.2.5.3.3 France Computational Pathology Market by End-use
        • 9.2.5.3.4 France Computational Pathology Market by Technology
      • 9.2.5.4 Russia Computational Pathology Market
        • 9.2.5.4.1 Russia Computational Pathology Market by Component
        • 9.2.5.4.2 Russia Computational Pathology Market by Application
        • 9.2.5.4.3 Russia Computational Pathology Market by End-use
        • 9.2.5.4.4 Russia Computational Pathology Market by Technology
      • 9.2.5.5 Spain Computational Pathology Market
        • 9.2.5.5.1 Spain Computational Pathology Market by Component
        • 9.2.5.5.2 Spain Computational Pathology Market by Application
        • 9.2.5.5.3 Spain Computational Pathology Market by End-use
        • 9.2.5.5.4 Spain Computational Pathology Market by Technology
      • 9.2.5.6 Italy Computational Pathology Market
        • 9.2.5.6.1 Italy Computational Pathology Market by Component
        • 9.2.5.6.2 Italy Computational Pathology Market by Application
        • 9.2.5.6.3 Italy Computational Pathology Market by End-use
        • 9.2.5.6.4 Italy Computational Pathology Market by Technology
      • 9.2.5.7 Rest of Europe Computational Pathology Market
        • 9.2.5.7.1 Rest of Europe Computational Pathology Market by Component
        • 9.2.5.7.2 Rest of Europe Computational Pathology Market by Application
        • 9.2.5.7.3 Rest of Europe Computational Pathology Market by End-use
        • 9.2.5.7.4 Rest of Europe Computational Pathology Market by Technology
  • 9.3 Asia Pacific Computational Pathology Market
    • 9.3.1 Asia Pacific Computational Pathology Market by Component
      • 9.3.1.1 Asia Pacific Software Market by Country
      • 9.3.1.2 Asia Pacific Services Market by Country
    • 9.3.2 Asia Pacific Computational Pathology Market by Application
      • 9.3.2.1 Asia Pacific Disease Diagnosis Market by Country
      • 9.3.2.2 Asia Pacific Drug Discovery & Development Market by Country
      • 9.3.2.3 Asia Pacific Academic Research Market by Country
    • 9.3.3 Asia Pacific Computational Pathology Market by End-use
      • 9.3.3.1 Asia Pacific Hospitals and Diagnostic Labs Market by Country
      • 9.3.3.2 Asia Pacific Biotechnology & Pharmaceutical Companies Market by Country
      • 9.3.3.3 Asia Pacific Academic and Research Institutes Market by Country
      • 9.3.3.4 Asia Pacific Other End-use Market by Country
    • 9.3.4 Asia Pacific Computational Pathology Market by Technology
      • 9.3.4.1 Asia Pacific Machine Learning (ML) Market by Country
      • 9.3.4.2 Asia Pacific Computational Pathology Market by Machine Learning (ML) Type
        • 9.3.4.2.1 Asia Pacific Deep Learning Market by Country
        • 9.3.4.2.2 Asia Pacific Other Machine Learning (ML) Market by Country
      • 9.3.4.3 Asia Pacific Computer Vision Market by Country
      • 9.3.4.4 Asia Pacific Natural Language Processing (NLP) Models Market by Country
      • 9.3.4.5 Asia Pacific Other Technology Market by Country
    • 9.3.5 Asia Pacific Computational Pathology Market by Country
      • 9.3.5.1 China Computational Pathology Market
        • 9.3.5.1.1 China Computational Pathology Market by Component
        • 9.3.5.1.2 China Computational Pathology Market by Application
        • 9.3.5.1.3 China Computational Pathology Market by End-use
        • 9.3.5.1.4 China Computational Pathology Market by Technology
        • 9.3.5.1.5 China Computational Pathology Market by Machine Learning (ML) Type
      • 9.3.5.2 Japan Computational Pathology Market
        • 9.3.5.2.1 Japan Computational Pathology Market by Component
        • 9.3.5.2.2 Japan Computational Pathology Market by Application
        • 9.3.5.2.3 Japan Computational Pathology Market by End-use
        • 9.3.5.2.4 Japan Computational Pathology Market by Technology
      • 9.3.5.3 India Computational Pathology Market
        • 9.3.5.3.1 India Computational Pathology Market by Component
        • 9.3.5.3.2 India Computational Pathology Market by Application
        • 9.3.5.3.3 India Computational Pathology Market by End-use
        • 9.3.5.3.4 India Computational Pathology Market by Technology
      • 9.3.5.4 South Korea Computational Pathology Market
        • 9.3.5.4.1 South Korea Computational Pathology Market by Component
        • 9.3.5.4.2 South Korea Computational Pathology Market by Application
        • 9.3.5.4.3 South Korea Computational Pathology Market by End-use
        • 9.3.5.4.4 South Korea Computational Pathology Market by Technology
      • 9.3.5.5 Singapore Computational Pathology Market
        • 9.3.5.5.1 Singapore Computational Pathology Market by Component
        • 9.3.5.5.2 Singapore Computational Pathology Market by Application
        • 9.3.5.5.3 Singapore Computational Pathology Market by End-use
        • 9.3.5.5.4 Singapore Computational Pathology Market by Technology
      • 9.3.5.6 Malaysia Computational Pathology Market
        • 9.3.5.6.1 Malaysia Computational Pathology Market by Component
        • 9.3.5.6.2 Malaysia Computational Pathology Market by Application
        • 9.3.5.6.3 Malaysia Computational Pathology Market by End-use
        • 9.3.5.6.4 Malaysia Computational Pathology Market by Technology
      • 9.3.5.7 Rest of Asia Pacific Computational Pathology Market
        • 9.3.5.7.1 Rest of Asia Pacific Computational Pathology Market by Component
        • 9.3.5.7.2 Rest of Asia Pacific Computational Pathology Market by Application
        • 9.3.5.7.3 Rest of Asia Pacific Computational Pathology Market by End-use
        • 9.3.5.7.4 Rest of Asia Pacific Computational Pathology Market by Technology
  • 9.4 LAMEA Computational Pathology Market
    • 9.4.1 LAMEA Computational Pathology Market by Component
      • 9.4.1.1 LAMEA Software Market by Country
      • 9.4.1.2 LAMEA Services Market by Country
    • 9.4.2 LAMEA Computational Pathology Market by Application
      • 9.4.2.1 LAMEA Disease Diagnosis Market by Country
      • 9.4.2.2 LAMEA Drug Discovery & Development Market by Country
      • 9.4.2.3 LAMEA Academic Research Market by Country
    • 9.4.3 LAMEA Computational Pathology Market by End-use
      • 9.4.3.1 LAMEA Hospitals and Diagnostic Labs Market by Country
      • 9.4.3.2 LAMEA Biotechnology & Pharmaceutical Companies Market by Country
      • 9.4.3.3 LAMEA Academic and Research Institutes Market by Country
      • 9.4.3.4 LAMEA Other End-use Market by Country
    • 9.4.4 LAMEA Computational Pathology Market by Technology
      • 9.4.4.1 LAMEA Machine Learning (ML) Market by Country
      • 9.4.4.2 LAMEA Computational Pathology Market by Machine Learning (ML) Type
        • 9.4.4.2.1 LAMEA Deep Learning Market by Country
        • 9.4.4.2.2 LAMEA Other Machine Learning (ML) Market by Country
      • 9.4.4.3 LAMEA Computer Vision Market by Country
      • 9.4.4.4 LAMEA Natural Language Processing (NLP) Models Market by Country
      • 9.4.4.5 LAMEA Other Technology Market by Country
    • 9.4.5 LAMEA Computational Pathology Market by Country
      • 9.4.5.1 Brazil Computational Pathology Market
        • 9.4.5.1.1 Brazil Computational Pathology Market by Component
        • 9.4.5.1.2 Brazil Computational Pathology Market by Application
        • 9.4.5.1.3 Brazil Computational Pathology Market by End-use
        • 9.4.5.1.4 Brazil Computational Pathology Market by Technology
      • 9.4.5.2 Argentina Computational Pathology Market
        • 9.4.5.2.1 Argentina Computational Pathology Market by Component
        • 9.4.5.2.2 Argentina Computational Pathology Market by Application
        • 9.4.5.2.3 Argentina Computational Pathology Market by End-use
        • 9.4.5.2.4 Argentina Computational Pathology Market by Technology
      • 9.4.5.3 UAE Computational Pathology Market
        • 9.4.5.3.1 UAE Computational Pathology Market by Component
        • 9.4.5.3.2 UAE Computational Pathology Market by Application
        • 9.4.5.3.3 UAE Computational Pathology Market by End-use
        • 9.4.5.3.4 UAE Computational Pathology Market by Technology
      • 9.4.5.4 Saudi Arabia Computational Pathology Market
        • 9.4.5.4.1 Saudi Arabia Computational Pathology Market by Component
        • 9.4.5.4.2 Saudi Arabia Computational Pathology Market by Application
        • 9.4.5.4.3 Saudi Arabia Computational Pathology Market by End-use
        • 9.4.5.4.4 Saudi Arabia Computational Pathology Market by Technology
      • 9.4.5.5 South Africa Computational Pathology Market
        • 9.4.5.5.1 South Africa Computational Pathology Market by Component
        • 9.4.5.5.2 South Africa Computational Pathology Market by Application
        • 9.4.5.5.3 South Africa Computational Pathology Market by End-use
        • 9.4.5.5.4 South Africa Computational Pathology Market by Technology
      • 9.4.5.6 Nigeria Computational Pathology Market
        • 9.4.5.6.1 Nigeria Computational Pathology Market by Component
        • 9.4.5.6.2 Nigeria Computational Pathology Market by Application
        • 9.4.5.6.3 Nigeria Computational Pathology Market by End-use
        • 9.4.5.6.4 Nigeria Computational Pathology Market by Technology
      • 9.4.5.7 Rest of LAMEA Computational Pathology Market
        • 9.4.5.7.1 Rest of LAMEA Computational Pathology Market by Component
        • 9.4.5.7.2 Rest of LAMEA Computational Pathology Market by Application
        • 9.4.5.7.3 Rest of LAMEA Computational Pathology Market by End-use
        • 9.4.5.7.4 Rest of LAMEA Computational Pathology Market by Technology

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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