UK Artificial Intelligence (AI) in Medical Imaging Market Report 2022 to 2030

UK Artificial Intelligence (AI) in Medical Imaging Market Analysis

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UK Artificial Intelligence (AI) in Medical Imaging market size was valued at $39 Mn in 2022 and is estimated to expand at a compound annual growth rate (CAGR) of 33.4% from 2022 to 2030 and will reach $391 Mn. The market is segmented by AI technology, solution, modality, application, and end User. The UK Artificial Intelligence (AI) in the Medical Imaging market will grow because AI technologies can help improve the accuracy and efficiency of medical imaging, leading to better patient outcomes and reduced healthcare costs. Some of the key players in this market are Optellum, Kheiron Medical, Aidoc, Sophia Genetics, Ultromics, Brainomix, MaxQ AI, Faculty, Sensyne Health, Feedback Medical, Cambridge Medical Imaging, Perspectum, Oxipit, Qure.ai, Quantib, Imagen, Mirada Medical, Kromek Group, GTN, 4D Imaging, and others.

ID: IN10GLDH023 CATEGORY: Digital Health GEOGRAPHY: UK AUTHOR: Chandani Patel

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UK Artificial Intelligence (AI) in Medical Imaging

Market Executive Summary

UK Artificial Intelligence (AI) in Medical Imaging market size was valued at $39 Mn in 2022 and is estimated to expand at a compound annual growth rate (CAGR) of 33.4% from 2022 to 2030 and will reach $ 391. The UK government has made significant investments in healthcare technology, including AI, in recent years. In November 2020, the UK government announced a $3.56 Bn investment in the National Health Service (NHS) to support the implementation of new technology, including AI. This funding will be used to upgrade existing technology infrastructure and to develop new AI-powered tools for use in healthcare.

In addition to government investment, private sector investment in AI in healthcare is also growing in the UK. In 2019, UK healthcare AI startups raised a record-breaking $237.10 Mn in funding, indicating a growing interest in the potential of AI in healthcare. While the exact amount of healthcare spending specifically on AI technology in the UK is difficult to quantify, it is clear that the government and private sector are both investing heavily in this area. As the benefits of AI in healthcare become increasingly apparent, it is likely that this investment will continue to grow in the coming years.

Artificial Intelligence (AI) in Medical Imaging is an emerging field that is transforming the way medical images are analyzed, interpreted, and used for diagnosis and treatment. In the UK, there has been growing interest and investment in AI-powered medical imaging technologies in recent years, with several startups and established companies developing innovative solutions for various medical imaging applications. One of the primary drivers of the AI in Medical Imaging market in the UK is the increasing demand for advanced diagnostic tools, particularly in the areas of cancer and cardiovascular disease. AI technologies can help improve the accuracy and efficiency of medical imaging, leading to better patient outcomes and reduced healthcare costs.

The use of Artificial Intelligence (AI) in Medical Imaging is not limited to any specific region in the UK, and it is being implemented and researched in various regions across the country. Here are some examples of regions in the UK where AI in Medical Imaging is being used for example, London is a hub for AI research and development, and several startups and established companies in the city are developing AI-powered medical imaging solutions. The London Medical Imaging and AI Centre for Value-Based Healthcare is a research center that is focused on developing AI tools for cancer diagnosis and treatment.

The University of Manchester has a dedicated research center for medical imaging, and researchers there are using AI to improve the accuracy of breast cancer screening. Additionally, The University of Oxford has developed an AI-powered imaging technology called HeartFlow, which uses AI to create 3D models of the heart and can help diagnose and treat coronary artery disease.

The University of Edinburgh has a research center focused on AI and medical imaging, and researchers there are developing AI algorithms to improve the diagnosis of prostate cancer. Furthermore, Cambridge is home to several AI startups and established companies that are developing medical imaging solutions. For example, Cambridge-based startup Optellum is using AI to improve the diagnosis of lung cancer. These are just a few examples of regions in the UK where AI in Medical Imaging is being used. The implementation of AI in medical imaging is a growing trend across the UK, and it is expected to continue to expand in the coming years.

uk AI in medical imaging market

Market Dynamics

Market Growth Drivers

The UK Artificial Intelligence (AI) in Medical Imaging market is driven by several factors, including increasing demand for advanced diagnostic tools, growing investment in AI research and development, and a supportive regulatory framework. AI technologies can help improve the accuracy and efficiency of medical imaging, leading to better patient outcomes and reduced healthcare costs. The increasing prevalence of chronic diseases such as cancer and cardiovascular disease is also driving demand for AI-powered imaging solutions.

Market restraints:

the market faces several restraints, including data privacy concerns, limited availability of annotated medical images, and the high cost of AI technology. The integration of AI into existing healthcare systems can also pose challenges, including workforce retraining, data management, and regulatory compliance. Additionally, the COVID-19 pandemic has created disruptions in healthcare systems and reduced funding for research and development, which may impact the growth of the AI in Medical Imaging market. Despite these challenges, the market is expected to continue to grow as AI technology advances and its benefits become more widely recognized in the healthcare industry.

Competitive Landscape

Key Players

Optellum (Oxford, UK)
Kheiron Medical (London, UK)
Aidoc (London, UK)
Sophia Genetics (London, UK)
Ultromics (Oxford, UK)
Brainomix (Oxford, UK)
MaxQ AI (London, UK)
Faculty (London, UK)
Sensyne Health (Oxford, UK)
Feedback Medical (Cambridge, UK)
Cambridge Medical Imaging (Cambridge, UK)
Perspectum (Oxford, UK)
Oxipit (London, UK)
Qure.ai (London, UK)
Quantib (London, UK)
Imagen (London, UK)
Mirada Medical (Oxford, UK)
Kromek Group (Sedgefield, UK)
GTN (London, UK)
4D Imaging (London, UK)
Siemens Healthineers (Germany)
GE Healthcare (USA)
Philips Healthcare (Netherlands)
Fujifilm (Japan)
Canon Medical Systems Europe (Japan)
Hologic (USA)
Samsung Healthcare (South Korea)
IBM Watson Health (USA)
NVIDIA (USA)
Intel Corporation (USA)
Google Health (USA)

Recent Developments

March 2021: Kheiron Medical, a UK-based AI medical imaging startup, announced it had raised $22 Mn in funding to expand its breast cancer screening AI technology.

February 2021: The University of Oxford announced that its AI-powered imaging technology had been approved for use in the NHS. The technology, called HeartFlow, uses AI to create 3D models of the heart and can help diagnose and treat coronary artery disease.

Healthcare Policies and Regulatory Landscape

Policy changes and Reimbursement scenario

The UK has several regulations and guidelines in place regarding the use of Artificial Intelligence (AI) in Medical Imaging. The Medicines and Healthcare products Regulatory Agency (MHRA) regulates medical devices, including those that incorporate AI. Manufacturers must comply with safety and effectiveness requirements and obtain the necessary approvals before bringing their products to market.

The General Data Protection Regulation (GDPR) outlines requirements for the processing of personal data, including medical images, in the EU. This regulation applies to AI applications in medical imaging that process personal data.

The National Institute for Health and Care Excellence (NICE) provides guidelines on the use of AI in healthcare. These guidelines aim to promote safe and effective use of AI in healthcare while highlighting areas that require further research and development.

The Royal College of Radiologists (RCR) has developed guidelines for the use of AI in radiology. These guidelines provide recommendations on the ethical, legal, and technical aspects of AI use in radiology.

The NHS AI Lab was established to support the safe and effective implementation of AI in healthcare. The lab provides a platform for collaboration between the NHS, industry, and academia to drive innovation and improve patient outcomes.

1. Executive Summary
1.1 Digital Health Overview
1.2 Global Scenario
1.3 Country Overview
1.4 Healthcare Scenario in Country
1.5 Digital Health Policy in Country
1.6 Recent Developments in the Country

2. Market Size and Forecasting
2.1 Market Size (With Excel and Methodology)
2.2 Market Segmentation (Check all Segments in Segmentation Section)

3. Market Dynamics
3.1 Market Drivers
3.2 Market Restraints

4. Competitive Landscape
4.1 Major Market Share

4.2 Key Company Profile (Check all Companies in the Summary Section)

4.2.1 Company
4.2.1.1 Overview
4.2.1.2 Product Applications and Services
4.2.1.3 Recent Developments
4.2.1.4 Partnerships Ecosystem
4.2.1.5 Financials (Based on Availability)

5. Reimbursement Scenario
5.1 Reimbursement Regulation
5.2 Reimbursement Process for Diagnosis
5.3 Reimbursement Process for Treatment

6. Methodology and Scope

Artificial Intelligence (AI) in Medical Imaging Market Segmentation

By AI Technology

Deep Learning
Natural Language Processing (NLP)
Others

By Solution

Software Tools/ Platform
Services
- Integration
- Deployment

By Modality

When compared to CT scans, magnetic resonance imaging can produce pictures that are free of imperfections. Due to its efficiency in obtaining details and better-quality pictures of soft tissues, the MRI is frequently seen as a superior alternative to X-rays. Utilizing optical coherence tomography, three-dimensional interactions between the retina and membranes are made possible in order to control the vitreoretinal disease.

CT Scan
MRI
X-rays
Ultrasound Imaging
Nuclear Imaging

By Application

The market is dominated by the digital pathology segment, which can be linked to pathologists' rising productivity. A validation tool for image analytics is provided by digital pathology, helping pathologists process more slides in less time. This facilitates early illness identification and quicker therapy initiation. AI and digital pathology also assist doctors in making patient-centered decisions. The oncology market is also expected to grow in popularity as more individuals become aware of cancer and its increased incidence in the public. Personalized therapy is made possible by artificial intelligence algorithms that identify and comprehend the nature of malignancies. The second section focUses on AI-driven diagnostic imaging for the heart, brain, breast, and mouth.

Digital Pathology
Oncology
Cardiovascular
Neurology
Lung (Respiratory System)
Breast (Mammography)
Liver (GI)
Oral Diagnostics
Other

By End Use

The market is dominated by the healthcare sector. This is becaUse hospitals are widely dispersed and accessible; hence, many patients like hospitals. The market for medical imaging AI is also anticipated to benefit from favorable reimbursement regulations. During the anticipated time, diagnostic centers are anticipated to grow in popularity. This may be attributable to elements including rising patient awareness and a desire for diagnostic procedures and tests, all of which are fueling the market's expansion. Due to its ease in providing high-quality medical facilities in remote places, particularly rural ones, the ambulatory category is expected to develop at a quicker CAGR throughout the projection period. The availability of qualified surgeons and a surplUK of the necessary equipment are contributing to the expansion of the hospital market. Government assistance in emerging nations is likely to boost hospital infrastructure and technologies throughout the forecast period, which is anticipated to caUse the hospital segment to see growth.

Hospital and Healthcare Providers
Patients
Pharmaceuticals and Biotechnology Companies
Healthcare Payers
Others

Methodology for Database Creation

Our database offers a comprehensive list of healthcare centers, meticulously curated to provide detailed information on a wide range of specialties and services. It includes top-tier hospitals, clinics, and diagnostic facilities across 30 countries and 24 specialties, ensuring users can find the healthcare services they need.

Additionally, we provide a comprehensive list of Key Opinion Leaders (KOLs) based on your requirements. Our curated list captures various crucial aspects of the KOLs, offering more than just general information. Whether you're looking to boost brand awareness, drive engagement, or launch a new product, our extensive list of KOLs ensures you have the right experts by your side. Covering 30 countries and 36 specialties, our database guarantees access to the best KOLs in the healthcare industry, supporting strategic decisions and enhancing your initiatives.

How Do We Get It?

Our database is created and maintained through a combination of secondary and primary research methodologies.

1. Secondary Research

With many years of experience in the healthcare field, we have our own rich proprietary data from various past projects. This historical data serves as the foundation for our database. Our continuous process of gathering data involves:

Analyzing historical proprietary data collected from multiple projects.
Regularly updating our existing data sets with new findings and trends.
Ensuring data consistency and accuracy through rigorous validation processes.

With extensive experience in the field, we have developed a proprietary GenAI-based technology that is uniquely tailored to our organization. This advanced technology enables us to scan a wide array of relevant information sources across the internet. Our data-gathering process includes:

Searching through academic conferences, published research, citations, and social media platforms
Collecting and compiling diverse data to build a comprehensive and detailed database
Continuously updating our database with new information to ensure its relevance and accuracy

2. Primary Research

To complement and validate our secondary data, we engage in primary research through local tie-ups and partnerships. This process involves:

Collaborating with local healthcare providers, hospitals, and clinics to gather real-time data.
Conducting surveys, interviews, and field studies to collect fresh data directly from the source.
Continuously refreshing our database to ensure that the information remains current and reliable.
Validating secondary data through cross-referencing with primary data to ensure accuracy and relevance.

Combining Secondary and Primary Research

By integrating both secondary and primary research methodologies, we ensure that our database is comprehensive, accurate, and up-to-date. The combined process involves:

Merging historical data from secondary research with real-time data from primary research.
Conducting thorough data validation and cleansing to remove inconsistencies and errors.
Organizing data into a structured format that is easily accessible and usable for various applications.
Continuously monitoring and updating the database to reflect the latest developments and trends in the healthcare field.

Through this meticulous process, we create a final database tailored to each region and domain within the healthcare industry. This approach ensures that our clients receive reliable and relevant data, empowering them to make informed decisions and drive innovation in their respective fields.