According to FutureWise analysis the market for Artificial Intelligence in Digital Pathology in 2023 is US$ 0.33 billion, and is expected to reach US$ 1.17 billion by 2031 at a CAGR of 17%.
Digital pathology refers to the digitization of pathology processes, encompassing the acquisition, management, sharing, and interpretation of pathological information derived from digitized specimen slides. This field employs Whole Slide Imaging (WSI), also known as virtual microscopy, which transforms traditional microscopic slides into digital images for easier analysis, management, and sharing via Whole Slide Scanners. A Whole Slide Scanner is a high-end microscope specifically designed to capture these images using a built-in camera. The digitization of slides enhances the analysis process, reduces errors, provides better and magnified views, facilitates network sharing of slides, and supports remote primary diagnostic work, teleconsultation, and virtual education.
Artificial Intelligence (AI) refers to the intelligence demonstrated by machines that perform actions within specific environments to achieve particular goals. This groundbreaking technology is increasingly being applied in various fields, including digital pathology. The integration of AI with digital pathology has the potential to revolutionize image-based diagnostics. Intelligent algorithms can be developed to identify both general and specific patterns, enabling reliable predictions about patient diseases, including potential outcomes. This offers new levels of hope and care within the field of pathology.
The synergy between AI and digital pathology also leads to increased efficiency, shorter turnaround times, and a reduction in manual errors. AI-driven tools in digital pathology represent a significant advancement compared to traditional molecular and genomic tests, which are currently considered the primary "high-value" tests capable of predicting recurrence and treatment response. Traditional diagnostic methods often involve lengthy processing times and are susceptible to errors. In contrast, AI-based pathology utilizes automated diagnostic tools, delivering results more quickly and minimizing error risks through software quality control, while promoting a more holistic and collaborative approach to patient care.
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Artificial Intelligence in Digital Pathology Market Segmentation:
By Neural Network Type
- Convolutional Neural Networks
- Recurrent Neural Networks
- Generative Adversarial Networks
- MVPNet
- Reinforced Auto Zoom Net
By Product
- Scanners
- Software
- Communication Systems
- Storage Systems
By Type
- Human Pathology
- Veterinary Pathology
By Application
- Teleconsultation
- Disease Diagnosis
- Drug Discovery
- Training and Education
By End User
- Pharmaceutical and Biotechnology Companies
- Hospitals and Reference Laboratories
- Academic and Research Institutes
By Region
- North America
- Latin America
- Europe
- Asia-Pacific
- Middle East and Africa
Competitive Landscape in the Artificial Intelligence in Digital Pathology Market:
- Roche
- Leica Biosystems
- Hamamatsu Photonics
- Koninklijke Philips
- 3D Hsitech
- Apollo Enterprises Imaging
- Xifin
- Huron Digital Pathology
- Vision pharm
- Corista
- Indica Labs
- Objective Pathology Services
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**Objectives of this Study: **
- To provide a comprehensive analysis of the Artificial Intelligence in Digital Pathology Market By Neural Network Type, By Product, By Type, By Application, By End User and By Region.
- To offer detailed insights into factors such as drivers, restraints, trends, and opportunities, as well as segmental and regional influences on market growth.
- To evaluate current market trends and forecast micro-markets, presenting overall market projections in the form of data sets and PowerPoint presentations.
- To predict the market size in key regions, including North America, Europe, Asia Pacific, Latin America, and the Middle East and Africa.
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