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AI In Medical Imaging Market - Global Outlook & Forecast 2022-2027

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  • 335 Pages
  • June 2022
  • Region: Global
  • Arizton
  • ID: 5614358
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The constant increase in the number of diagnostic procedures and the decline in the number of radiologists, increasing work pressure on the radiologists, have increased the need for artificial intelligence adoption in the medical imaging space. The researchers are looking for multiple ways to implement artificial intelligence into medical imaging. The demand for artificial intelligence is constantly increasing in the medical imaging software market. From cardiac events, neurological conditions, fractures, or thoracic complications, artificial intelligence helps physicians to diagnose and provide treatment quickly. Implementing AI in medical imaging has enhanced medical screening, improved precision medicine software, reduced physicians' load, etc.

Technological Advancements Revolutionizing AI in Medical Imaging

  • There have been many technological advancements in AI-based medical imaging technologies, which have shown their increasing acceptance in high-income countries. Some of the improvements include the development of integrated rtiI software, which can directly be integrated into imaging equipment (MRI or CT scanner) which facilitates the automation of medical image analysis. Other advances include smartphone technology integration in AI in medical imaging in which front-line health workers could non-invasively screen for various conditions by leveraging a smartphone.
  • AI in medical imaging has drawn the attention of several radiologists worldwide. It gives faster and more accurate results and reduces diagnostic errors at reduced costs compared to traditional medical imaging methods. Thus, radiologists believe that AI in medical imaging may bring an enormous opportunity for its increasing implementation in the upcoming years.
  • In recent years, many large established companies, such as GE Healthcare and Siemens Healthineers, have enabled themselves to grow the AI in the medical imaging market by making huge investments for increasing partnerships and acquisitions. Other large healthcare-related or software companies not previously invested in health care, such as Thermo Fisher Scientific and Paraxel, have started making huge investments in the market.

Vendor's Activity in AI-Based Medical Imaging Market

Siemens Healthineers, General Electric (GE) Company, Koninklijke Philips, and IBM Watson Health are the major players in the global AI in the medical imaging market. International players focus on developing innovative products with advanced technologies and expanding their product portfolio to remain competitive. They are continuously investing extensively in R&D to expand their product portfolio. Manufacturers such as GE Healthcare constantly focus on introducing new products with innovative technology platforms opening the platform (Edison Developer Program) for other companies offering artificial intelligence technologies to scale and deploy their developed applications across GE Healthcare's customer base.

Many major players are engaged in strategic acquisitions and partnerships that continue to be a competitive strategy for the key players, thus helping them grow inorganically. Innovative product approvals coupled with R&D activities are also helping the vendors to expand their presence, enhance growth, and sustain their position in the global market. In 2021, more than 30 countries approved AI in medical imaging technologies that are FDA and CE approved.

There is increasing funding and investments by public and private entities, including large companies, which is also one of the major driving factors of AI in the medical imaging market. For instance, more than 20 start-ups from various regions have received funds to develop AI-based medical imaging technologies.


  • North America holds a dominant position in artificial intelligence in the medical imaging market. High adoption of advanced technologies is the primary factor for its larger industry share. In addition, the strong presence of the key players in the region is also a contributor to North America for holding a high market share.
  • Europe is the second-largest market for AI-based medical imaging. The presence of prominent market players and high healthcare spending are the primary factors for the significant market share in this region. The industry in Europe is mainly driven by the increasing collaborative research with extensive funding from the government. Increasing funding and investments are also driving the AI-based medical imaging market in the region.
  • The adoption rate of advanced artificial intelligence technologies in the medical imaging sector is still emerging in the Asia-pacific region. In recent years, there has been a noticeable investment and funding made by government and corporations and increasing collaborations and partnerships among the companies, research centers, and institutes. Due to these factors, the industry is growing exponentially in this region.
  • Lack of awareness of the importance of artificial intelligence in medical imaging, radiologists' job insecurity, a lack of sufficient IT infrastructure, a lack of proper training and knowledge among radiologists, concerns about data security, and a shortage of skilled professionals are all factors contributing to the industry's slow growth in Latin America, the Middle East, and Africa.
  • Among all the regions, APAC could witness the highest growth over the forecast period, with a CAGR of 51.06% in the global industry. The increasing prevalence of chronic diseases and diagnostic errors has opened enormous opportunities for APAC medical imaging AI market growth.

Segmentation by Geography

  • North America
  • US
  • Canada
  • Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • APAC
  • Japan
  • China
  • India
  • Australia
  • South Korea
  • Latin America
  • Brazil
  • Mexico
  • Argentina
  • Middle East And Africa
  • Turkey
  • Saudi Arabia
  • UAE
  • South Africa


Hospitals are purchasing the artificial intelligence medical software suits as a complete package for the usage or taking up one program at a time which is used the most in the industry. The diagnostic imaging center's significant revenue generation is through imaging procedures, and they are primarily involved in implementing advanced products, which will attract customers. For instance, AI in medical imaging, along with clinical data, is helping physicians to predict heart attacks in patients accurately.

Neurology has accounted for the dominating share in the industry. The majority of the initial artificial intelligence product development focuses on downstream processing. This Downstream processing majorly includes artificial intelligence for segmentation, detecting anatomical structures, and quantifying a range of pathologies. Conditions like intracranial hemorrhage, ischemic stroke, primary brain tumors, cerebral metastases, and abnormal white matter signal intensities, which were unmet needs in the industry, has become commercially available solution within the radiology industry.

AI in medical imaging, especially cardiovascular magnetic resonance (CMR), is revolutionized by providing deep learning solutions, especially for image acquisitions, reconstructions, and analysis, which helps in supporting clinical decision-making. CMR is an established tool for routine clinical decision-making, including diagnosis, follow-up, real-time procedures, and pre-procedure planning.

Deep learning methods have enabled more tremendous success in medical image analysis. They have helped high accuracy, efficiency, stability, and scalability. Artificial intelligence tools have become assistive tools in medicine with benefits like error reduction, accuracy, fast computing, and better diagnostics. Natural language processing, Computer Vision, and Context-Aware Computing technologies are also used to create new analysis methods for medical imaging products.

In 2021, Philips showcased its new AI-enabled CT imaging portfolio. Their new CT 5100 with smart workflow application applies artificial intelligence at every step of CT image processing.

Siemens Healthineers's AI-Rad companion chest CT detects and highlights lung nodules. The tumor burden is automatically calculated.

In addition, AI-Rad companion chest X-Ray played a significant role in patient management during the COVID-19 pandemic. The artificial intelligence-Rad companion file automatically processes upright chest X-ray images, pneumothorax, nodule detection, etc. This indicates the consolidations and atelectasis. This indicates the sign of pneumonia caused by the COVID-19 virus.

Artificial intelligence in CT scans and MRI dominated the industry, as much medical imaging using artificial intelligence tools falls into these modality categories. However, artificial intelligence in ultrasound and detecting mammography is largely adopted in the industry.

Segmentation by Technology

  • Deep Learning
  • NIP
  • Others

Segmentation by Application

  • Neurology
  • Respiratory & Pulmonary
  • Cardiology
  • Breast Screening
  • Orthopedic
  • Others

Segmentation by Modalities

  • CT
  • MRI
  • X-RAY
  • Ultrasound
  • Nuclear Imaging

Segmentation by End-User

  • Hospitals
  • Diagnostic Imaging Centers
  • Others

Key Vendors

  • General Electric
  • Siemens Healthineers
  • Koninklijke Philips
  • IBM Watson Health

Other Prominent Vendors

  • Agfa-Gevaert Group/Agfa HealthCare
  • Arterys
  • Avicenna.AI
  • AZmed
  • Butterfly Network
  • Caption Health
  • CellmatiQ
  • dentalXrai
  • Digital Diagnostics
  • EchoNous
  • HeartVista
  • iCAD
  • Lunit
  • Mediaire
  • MEDO
  • Nanox Imaging
  • Paige AI
  • Perimeter Medical Imaging AI
  • Predible Health
  • 1QB Information Technology
  • Qure.ai
  • Quantib
  • Quibim
  • Renalytix
  • Therapixel
  • Ultromics
  • Viz.ai
  • VUNO


1. How Big is the Artificial Intelligence in Medical Imaging Market?
2. What is the Growth Rate of the AI in Medical Imaging Market?
3. Who are is the Key Players in the AI in Medical Imaging Market?
4. What are is the Latest Trends in the AI-Based Medical Imaging Market?
5. Which Region Is Expected to hold the largest share in the AI-Based Medical Imaging Market?

Table of Contents

1 Research Methodology2 Research Objectives3 Research Process
4 Scope & Coverage
4.1 Market Definition
4.2 Base Year
4.3 Scope of the Study
5 Report Assumptions & Caveats
5.1 Key Caveats
5.2 Currency Conversion
5.3 Market Derivation
6 Market at a Glance
7 Introduction
7.1 Background
7.2 Artificial Intelligence in Healthcare Industry
7.3 Artificial Intelligence in Medical Imaging
8 Market Opportunities & Trends
8.1 Technological Advances in Ai-Based Medical Imaging
8.2 Increasing Adoption of Ai-Based Medical Imaging in Developed Countries
8.3 Growing Inclination of Radiologists Toward Ai-Based Medical Imaging
9 Market Growth Enablers
9.1 Rise in Number of Diagnostic Procedures
9.2 Expanding Investment Opportunities in Ai-Based Medical Imaging
9.3 Rise in Approved/Commercial Ai-Based Medical Imaging Platforms
9.4 Developments in Ai, Cloud-Based, & Hybrid Imaging Solutions
10 Market Restraints
10.1 Lower Adoption of Ai-Based Medical Imaging in Lmics
10.2 Lack of Integration and Practical Applications of Ai in Medical Imaging
10.3 Concerns Associated With Data Breaches in Ai-Based Medical Imaging
11 Market Landscape
11.1 Market Overview
11.2 Market Size & Forecast
11.3 Five Forces Analysis
12 Technology
12.1 Market Snapshot & Growth Engine
12.2 Market Overview
12.3 Deep Learning
12.4 Nlp
12.5 Others
13 Application
13.1 Market Snapshot & Growth Engine
13.2 Market Overview
13.3 Neurology
13.4 Respiratory & Pulmonary
13.5 Cardiology
13.6 Breast Cancer
13.7 Orthopedic
13.8 Others
14 Modality
14.1 Market Snapshot & Growth Engine
14.2 Market Overview
14.3 Ct
14.4 Mri
14.5 X-Ray
14.6 Ultrasound
14.7 Nuclear Imaging
15 End-user
15.1 Market Snapshot & Growth Engine
15.2 Market Overview
15.3 Hospitals
15.4 Diagnostic Imaging Centers
15.5 Others
16 Geography
16.1 Market Snapshot & Growth Engine
16.2 Geographic Overview
17 North America
17.1 Market Overview
17.2 Market Size & Forecast
17.3 North America: Technology Segmentation
17.4 North America: Application Segmentation
17.5 North America: Modality Segmentation
17.6 North America: End-User Segmentation
17.7 Key Countries
18 Europe
18.1 Market Overview
18.2 Market Size & Forecast
18.3 Europe: Technology Segmentation
18.4 Europe: Application Segmentation
18.5 Europe: Modality Segmentation
18.6 Europe: End-User Segmentation
18.7 Key Countries
19 Apac
19.1 Market Overview
19.2 Market Size & Forecast
19.3 Apac: Technology Segmentation
19.4 Apac: Application Segmentation
19.5 Apac: Modality Segmentation
19.6 Apac: End-User Segmentation
19.7 Key Countries
20. Latin America
20.1 Market Overview
20.2 Market Size & Forecast
20.3 Latin America: Technology Segmentation
20.4 Latin America: Application Segmentation
20.5 Latin America: Modalities Segmentation
20.6 Latin America: End-User Segmentation
20.7 Key Countries
21. Middle East & Africa
21.1 Market Overview
21.2 Market Size & Forecast
21.3 Middle East & Africa: Technology Segmentation
21.4 Middle East & Africa: Application Segmentation
21.5 Middle East & Africa: Modalities Segmentation
21.6 Middle East & Africa: End-User Segmentation
21.7 Key Countries
22. Competitive Landscape
22.1 Competition Overview
22.2 Market Share Analysis
23. Key Company Profiles
23.1 General Electric
23.2 Siemens Healthineers
23.3 Koninklijke Philips
23.4 IBM Watson Health
24. Other Prominent Vendors
24.1 Agfa-Gevaert Group
24.2 Arterys
24.3 Avicenna.Ai
24.4 Azmed
24.5 Butterfly Network
24.6 Caption Health
24.7 Cellmatiq
24.8 Dentalxrai
24.9 Digital Diagnostics
24.10 Echonous
24.11 Gleamer
24.12 Heartvista
24.13 Icad
24.14 Lunit
24.15 Mediaire
24.16 Medo
24.17 Nanox Imaging
24.18 Paige Ai
24.19 Perimeter Medical Imaging Ai
24.20 Predible Health
24.21 1Qb Information Technologies
24.22 Quri.Ai
24.23 Quantib
24.24 Qlarity Imaging
24.25 Quibim
24.26 Renalytix
24.27 Therapixel
24.28 Ultromics
24.29 Viz.Ai
24.30 Vuno
25. Report Summary
25.1 Key Takeaways
25.2 Strategic Recommendations
26. Quantitative Summary
26.1 Market by Geography
26.2 Market by Technology
26.3 Market by Application
26.4 Market by Modality
26.5 Market by End-user
26.6 North America by Technology
26.7 North America by Application
26.8 North America by Modality
26.9 North America by End-user
26.10 Europe by Technology
26.11 Europe by Application
26.12 Europe by Modality
26.13 Europe by End-user
26.14 APAC by Technology
26.15 APAC by Application
26.16 APAC by Modality
26.17 APAC by End-user
26.18 Latin America by Technology
26.19 Latin America by Application
26.20 Latin America by Modality
26.21 Latin America by End-user
26.22 Middle East and Africa by Technology
26.23 Middle East and Africa by Application
26.24 Middle East and Africa by Modality
26.25 Middle East and Africa by End-user
27. Appendix
27.1 Abbreviations

Companies Mentioned

  • General Electric
  • Siemens Healthineers
  • Koninklijke Philips
  • IBM Watson Health
  • Agfa-Gevaert Group/Agfa HealthCare
  • Arterys
  • Avicenna.AI
  • AZmed
  • Butterfly Network
  • Caption Health
  • CellmatiQ
  • dentalXrai
  • Digital Diagnostics
  • EchoNous
  • HeartVista
  • iCAD
  • Lunit
  • Mediaire
  • MEDO
  • Nanox Imaging
  • Paige AI
  • Perimeter Medical Imaging AI
  • Predible Health
  • 1QB Information Technology
  • Qure.ai
  • Quantib
  • Quibim
  • Renalytix
  • Therapixel
  • Ultromics
  • Viz.ai
  • VUNO


Our research comprises a mix of primary and secondary research. The secondary research sources that are typically referred to include, but are not limited to, company websites, annual reports, financial reports, company pipeline charts, broker reports, investor presentations and SEC filings, journals and conferences, internal proprietary databases, news articles, press releases, and webcasts specific to the companies operating in any given market.

Primary research involves email interactions with the industry participants across major geographies. The participants who typically take part in such a process include, but are not limited to, CEOs, VPs, business development managers, market intelligence managers, and national sales managers. We primarily rely on internal research work and internal databases that we have populated over the years. We cross-verify our secondary research findings with the primary respondents participating in the study.