The AI in medical imaging market would grow at a CAGR of 36.87% over the predicted time frame. The market is expected to increase in value from US$ 1.7 Bn in 2022 to US$ 20.9 Bn in 2030.
The on AI in medical imaging Market, which provides a business strategy, research & development activities, concise outline of the market valuation, valuable insights pertaining to market share, size, supply chain analysis, competitive landscape and regional proliferation of this industry.
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A recent report provides crucial insights along with application based and forecast information in the Global AI in medical imaging Market. The report provides a comprehensive analysis of key factors that are expected to drive the growth of this market. This study also provides a detailed overview of the opportunities along with the current trends observed in the AI in medical imaging market.
A quantitative analysis of the industry is compiled for a period of 10 years in order to assist players to grow in the market. Insights on specific revenue figures generated are also given in the report, along with projected revenue at the end of the forecast period.
Companies and Manufacturers Covered
The study covers key players operating in the market along with prime schemes and strategies implemented by each player to hold high positions in the industry. Such a tough vendor landscape provides a competitive outlook of the industry, consequently existing as a key insight. These insights were thoroughly analysed and prime business strategies and products that offer high revenue generation capacities were identified. Key players of the global AI in medical imaging market are included as given below:
AI in medical imaging Market Key Players
- Agfa-Gevaert Group/Agfa HealthCare
- Arterys
- AI
- AZmed
- Butterfly Network
- Caption Health
- CellmatiQ
- dentalXrai
- Digital Diagnostics
- EchoNous
- GLEAMER
- HeartVista
- iCAD
- Lunit
- Mediaire
- MEDO
- Nanox Imaging
- Paige AI
- Perimeter Medical Imaging AI
- Predible Health
- 1QB Information Technology
- Qure.ai
- Quantib
- QLARITY IMAGING
- Quibim
- Renalytix
- Therapixel
- Ultromics
- Viz.ai
- VUNO
Market Segments
By AI Technology
- Deep Learning
- Natural Language Processing (NLP)
- Others
By Solution
- Software Tools/ Platform
- Services
- Integration
- Deployment
By Modality
- CT Scan
- MRI
- X-rays
- Ultrasound Imaging
- Nuclear Imaging
By Application
- Digital Pathology
- Oncology
- Cardiovascular
- Neurology
- Lung (Respiratory System)
- Breast (Mammography)
- Liver (GI)
- Oral Diagnostics
- Other
By End Use
- Hospital and Healthcare Providers
- Patients
- Pharmaceuticals and Biotechnology Companies
- Healthcare Payers
- Others
By Geography
- North America
- Europe
- Asia-Pacific
- Latin America
- Middle East & Africa (MEA)
Report Objectives
- To define, describe, and forecast the global AI in medical imaging market based on product, and region
- To provide detailed information regarding the major factors influencing the growth of the market (drivers, opportunities, and industry-specific challenges)
- To strategically analyze micromarkets1 with respect to individual growth trends, future prospects, and contributions to the total market
- To analyze opportunities in the market for stakeholders and provide details of the competitive landscape for market leaders
- To forecast the size of market segments with respect to four main regions—North America, Europe, Asia Pacific and the Rest of the World (RoW)2
- To strategically profile key players and comprehensively analyze their product portfolios, market shares, and core competencies3
- To track and analyze competitive developments such as acquisitions, expansions, new product launches, and partnerships in the AI in medical imaging market
Table of Content
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on AI in Medical Imaging Market
5.1. COVID-19 Landscape: AI in Medical Imaging Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global AI in Medical Imaging Market, By AI Technology
8.1. AI in Medical Imaging Market, by AI Technology, 2023-2032
8.1.1. Deep Learning
8.1.1.1. Market Revenue and Forecast (2023-2032)
8.1.2. Natural Language Processing (NLP)
8.1.2.1. Market Revenue and Forecast (2023-2032)
8.1.3. Others
8.1.3.1. Market Revenue and Forecast (2023-2032)
Chapter 9. Global AI in Medical Imaging Market, By Solution
9.1. AI in Medical Imaging Market, by Solution, 2023-2032
9.1.1. Software Tools/ Platform
9.1.1.1. Market Revenue and Forecast (2023-2032)
9.1.2. Services
9.1.2.1. Market Revenue and Forecast (2023-2032)
9.1.3. Integration
9.1.3.1. Market Revenue and Forecast (2023-2032)
9.1.4. Deployment
9.1.4.1. Market Revenue and Forecast (2023-2032)
Chapter 10. Global AI in Medical Imaging Market, By Modality
10.1. AI in Medical Imaging Market, by Modality, 2023-2032
10.1.1. CT Scan
10.1.1.1. Market Revenue and Forecast (2023-2032)
10.1.2. MRI
10.1.2.1. Market Revenue and Forecast (2023-2032)
10.1.3. X-rays
10.1.3.1. Market Revenue and Forecast (2023-2032)
10.1.4. Ultrasound Imaging
10.1.4.1. Market Revenue and Forecast (2023-2032)
10.1.5. Nuclear Imaging
10.1.5.1. Market Revenue and Forecast (2023-2032)
Chapter 11. Global AI in Medical Imaging Market, By Application
11.1. AI in Medical Imaging Market, by Application, 2023-2032
11.1.1. Digital Pathology
11.1.1.1. Market Revenue and Forecast (2023-2032)
11.1.2. Oncology
11.1.2.1. Market Revenue and Forecast (2023-2032)
11.1.3. Cardiovascular
11.1.3.1. Market Revenue and Forecast (2023-2032)
11.1.4. Neurology
11.1.4.1. Market Revenue and Forecast (2023-2032)
11.1.5. Lung (Respiratory System)
11.1.5.1. Market Revenue and Forecast (2023-2032)
11.1.6. Breast (Mammography)
11.1.6.1. Market Revenue and Forecast (2023-2032)
11.1.7. Liver (GI)
11.1.7.1. Market Revenue and Forecast (2023-2032)
11.1.8. Oral Diagnostics
11.1.8.1. Market Revenue and Forecast (2023-2032)
11.1.9. Other
11.1.9.1. Market Revenue and Forecast (2023-2032)
Chapter 12. Global AI in Medical Imaging Market, By End Use
12.1. AI in Medical Imaging Market, by End Use, 2023-2032
12.1.1. Hospital and Healthcare Providers
12.1.1.1. Market Revenue and Forecast (2023-2032)
12.1.2. Patients
12.1.2.1. Market Revenue and Forecast (2023-2032)
12.1.3. Pharmaceuticals and Biotechnology Companies
12.1.3.1. Market Revenue and Forecast (2023-2032)
12.1.4. Healthcare Payers
12.1.4.1. Market Revenue and Forecast (2023-2032)
12.1.5. Others
12.1.5.1. Market Revenue and Forecast (2023-2032)
Chapter 13. Global AI in Medical Imaging Market, Regional Estimates and Trend Forecast
13.1. North America
13.1.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.1.2. Market Revenue and Forecast, by Solution (2023-2032)
13.1.3. Market Revenue and Forecast, by Modality (2023-2032)
13.1.4. Market Revenue and Forecast, by Application (2023-2032)
13.1.5. Market Revenue and Forecast, by End Use (2023-2032)
13.1.6. U.S.
13.1.6.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.1.6.2. Market Revenue and Forecast, by Solution (2023-2032)
13.1.6.3. Market Revenue and Forecast, by Modality (2023-2032)
13.1.6.4. Market Revenue and Forecast, by Application (2023-2032)
13.1.6.5. Market Revenue and Forecast, by End Use (2023-2032)
13.1.7. Rest of North America
13.1.7.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.1.7.2. Market Revenue and Forecast, by Solution (2023-2032)
13.1.7.3. Market Revenue and Forecast, by Modality (2023-2032)
13.1.7.4. Market Revenue and Forecast, by Application (2023-2032)
13.1.7.5. Market Revenue and Forecast, by End Use (2023-2032)
13.2. Europe
13.2.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.2.2. Market Revenue and Forecast, by Solution (2023-2032)
13.2.3. Market Revenue and Forecast, by Modality (2023-2032)
13.2.4. Market Revenue and Forecast, by Application (2023-2032)
13.2.5. Market Revenue and Forecast, by End Use (2023-2032)
13.2.6. UK
13.2.6.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.2.6.2. Market Revenue and Forecast, by Solution (2023-2032)
13.2.6.3. Market Revenue and Forecast, by Modality (2023-2032)
13.2.7. Market Revenue and Forecast, by Application (2023-2032)
13.2.8. Market Revenue and Forecast, by End Use (2023-2032)
13.2.9. Germany
13.2.9.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.2.9.2. Market Revenue and Forecast, by Solution (2023-2032)
13.2.9.3. Market Revenue and Forecast, by Modality (2023-2032)
13.2.10. Market Revenue and Forecast, by Application (2023-2032)
13.2.11. Market Revenue and Forecast, by End Use (2023-2032)
13.2.12. France
13.2.12.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.2.12.2. Market Revenue and Forecast, by Solution (2023-2032)
13.2.12.3. Market Revenue and Forecast, by Modality (2023-2032)
13.2.12.4. Market Revenue and Forecast, by Application (2023-2032)
13.2.13. Market Revenue and Forecast, by End Use (2023-2032)
13.2.14. Rest of Europe
13.2.14.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.2.14.2. Market Revenue and Forecast, by Solution (2023-2032)
13.2.14.3. Market Revenue and Forecast, by Modality (2023-2032)
13.2.14.4. Market Revenue and Forecast, by Application (2023-2032)
13.2.15. Market Revenue and Forecast, by End Use (2023-2032)
13.3. APAC
13.3.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.3.2. Market Revenue and Forecast, by Solution (2023-2032)
13.3.3. Market Revenue and Forecast, by Modality (2023-2032)
13.3.4. Market Revenue and Forecast, by Application (2023-2032)
13.3.5. Market Revenue and Forecast, by End Use (2023-2032)
13.3.6. India
13.3.6.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.3.6.2. Market Revenue and Forecast, by Solution (2023-2032)
13.3.6.3. Market Revenue and Forecast, by Modality (2023-2032)
13.3.6.4. Market Revenue and Forecast, by Application (2023-2032)
13.3.7. Market Revenue and Forecast, by End Use (2023-2032)
13.3.8. China
13.3.8.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.3.8.2. Market Revenue and Forecast, by Solution (2023-2032)
13.3.8.3. Market Revenue and Forecast, by Modality (2023-2032)
13.3.8.4. Market Revenue and Forecast, by Application (2023-2032)
13.3.9. Market Revenue and Forecast, by End Use (2023-2032)
13.3.10. Japan
13.3.10.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.3.10.2. Market Revenue and Forecast, by Solution (2023-2032)
13.3.10.3. Market Revenue and Forecast, by Modality (2023-2032)
13.3.10.4. Market Revenue and Forecast, by Application (2023-2032)
13.3.10.5. Market Revenue and Forecast, by End Use (2023-2032)
13.3.11. Rest of APAC
13.3.11.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.3.11.2. Market Revenue and Forecast, by Solution (2023-2032)
13.3.11.3. Market Revenue and Forecast, by Modality (2023-2032)
13.3.11.4. Market Revenue and Forecast, by Application (2023-2032)
13.3.11.5. Market Revenue and Forecast, by End Use (2023-2032)
13.4. MEA
13.4.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.4.2. Market Revenue and Forecast, by Solution (2023-2032)
13.4.3. Market Revenue and Forecast, by Modality (2023-2032)
13.4.4. Market Revenue and Forecast, by Application (2023-2032)
13.4.5. Market Revenue and Forecast, by End Use (2023-2032)
13.4.6. GCC
13.4.6.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.4.6.2. Market Revenue and Forecast, by Solution (2023-2032)
13.4.6.3. Market Revenue and Forecast, by Modality (2023-2032)
13.4.6.4. Market Revenue and Forecast, by Application (2023-2032)
13.4.7. Market Revenue and Forecast, by End Use (2023-2032)
13.4.8. North Africa
13.4.8.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.4.8.2. Market Revenue and Forecast, by Solution (2023-2032)
13.4.8.3. Market Revenue and Forecast, by Modality (2023-2032)
13.4.8.4. Market Revenue and Forecast, by Application (2023-2032)
13.4.9. Market Revenue and Forecast, by End Use (2023-2032)
13.4.10. South Africa
13.4.10.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.4.10.2. Market Revenue and Forecast, by Solution (2023-2032)
13.4.10.3. Market Revenue and Forecast, by Modality (2023-2032)
13.4.10.4. Market Revenue and Forecast, by Application (2023-2032)
13.4.10.5. Market Revenue and Forecast, by End Use (2023-2032)
13.4.11. Rest of MEA
13.4.11.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.4.11.2. Market Revenue and Forecast, by Solution (2023-2032)
13.4.11.3. Market Revenue and Forecast, by Modality (2023-2032)
13.4.11.4. Market Revenue and Forecast, by Application (2023-2032)
13.4.11.5. Market Revenue and Forecast, by End Use (2023-2032)
13.5. Latin America
13.5.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.5.2. Market Revenue and Forecast, by Solution (2023-2032)
13.5.3. Market Revenue and Forecast, by Modality (2023-2032)
13.5.4. Market Revenue and Forecast, by Application (2023-2032)
13.5.5. Market Revenue and Forecast, by End Use (2023-2032)
13.5.6. Brazil
13.5.6.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.5.6.2. Market Revenue and Forecast, by Solution (2023-2032)
13.5.6.3. Market Revenue and Forecast, by Modality (2023-2032)
13.5.6.4. Market Revenue and Forecast, by Application (2023-2032)
13.5.7. Market Revenue and Forecast, by End Use (2023-2032)
13.5.8. Rest of LATAM
13.5.8.1. Market Revenue and Forecast, by AI Technology (2023-2032)
13.5.8.2. Market Revenue and Forecast, by Solution (2023-2032)
13.5.8.3. Market Revenue and Forecast, by Modality (2023-2032)
13.5.8.4. Market Revenue and Forecast, by Application (2023-2032)
13.5.8.5. Market Revenue and Forecast, by End Use (2023-2032)
Chapter 14. Company Profiles
14.1. Agfa-Gevaert Group/Agfa HealthCare
14.1.1. Company Overview
14.1.2. Product Offerings
14.1.3. Financial Performance
14.1.4. Recent Initiatives
14.2. Arterys
14.2.1. Company Overview
14.2.2. Product Offerings
14.2.3. Financial Performance
14.2.4. Recent Initiatives
14.3. AI
14.3.1. Company Overview
14.3.2. Product Offerings
14.3.3. Financial Performance
14.3.4. Recent Initiatives
14.4. AZmed
14.4.1. Company Overview
14.4.2. Product Offerings
14.4.3. Financial Performance
14.4.4. Recent Initiatives
14.5. Butterfly Network
14.5.1. Company Overview
14.5.2. Product Offerings
14.5.3. Financial Performance
14.5.4. Recent Initiatives
14.6. Caption Health
14.6.1. Company Overview
14.6.2. Product Offerings
14.6.3. Financial Performance
14.6.4. Recent Initiatives
14.7. CellmatiQ
14.7.1. Company Overview
14.7.2. Product Offerings
14.7.3. Financial Performance
14.7.4. Recent Initiatives
14.8. dentalXrai
14.8.1. Company Overview
14.8.2. Product Offerings
14.8.3. Financial Performance
14.8.4. Recent Initiatives
14.9. Digital Diagnostics
14.9.1. Company Overview
14.9.2. Product Offerings
14.9.3. Financial Performance
14.9.4. Recent Initiatives
14.10. EchoNous
14.10.1. Company Overview
14.10.2. Product Offerings
14.10.3. Financial Performance
14.10.4. Recent Initiatives
Chapter 15. Research Methodology
15.1. Primary Research
15.2. Secondary Research
15.3. Assumptions
Chapter 16. Appendix
16.1. About Us
16.2. Glossary of Terms
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