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

Canada Artificial Intelligence (AI) in Medical Imaging Market Analysis

$ 3999

Canada's Artificial Intelligence (AI) in Medical Imaging market size was valued at $120 Mn in 2022 and is estimated to expand at a compound annual growth rate (CAGR) of 35.4% from 2022 to 2030 and will reach $1356Mn. The market is segmented by AI technology, solution, modality, application, and end User. The Canada Artificial Intelligence (AI) in the Medical Imaging market will grow due to advances in AI and machine learning algorithms that are making it possible to develop more accurate and efficient medical imaging software. Some of the key players in this market are Imagia, Intelerad Medical Systems, Aifred Health, HeartForce Medical, Swift Medical, Resolution Health, Hooton AI (Vancouver, British Columbia) and others.

ID: IN10CADH023 CATEGORY: Digital Health GEOGRAPHY: Canada AUTHOR: Chandani Patel

Buy Now

Canada Artificial Intelligence (AI) in Medical Imaging

Market Executive Summary

Canada's Artificial Intelligence (AI) in Medical Imaging market size was valued at $120 Mn in 2022 and is estimated to expand at a compound annual growth rate (CAGR) of 35.4% from 2022-30 and will reach $1356Mn. According to the Canadian Institute for Health Information, healthcare spending in Canada reached $264 Bn in 2019, which represents approximately 11.6% of the country's GDP. Of this spending, the federal and provincial governments funded approximately 70%, with the remainder coming from private sources such as individuals and private insurance.

The Canadian government funds healthcare through a combination of federal and provincial/territorial programs, including the Canada Health Transfer (CHT), which provides funding to provinces and territories to support healthcare services. The federal government also provides funding for specific healthcare initiatives and programs, such as mental health and addiction services and home care. The use of artificial intelligence (AI) in healthcare, including medical imaging, has the potential to impact healthcare spending in Canada by improving efficiency and reducing the need for costly interventions.

AI has the potential to improve the efficiency and accuracy of medical imaging by assisting radiologists in analyzing and interpreting medical images. This can lead to faster and more accurate diagnoses, which can ultimately improve patient outcomes. Some examples of AI applications in medical imaging that have been studied and implemented in Canada such as, CAD software uses AI algorithms to analyze medical images and identify areas that may indicate disease. CAD has been used in mammography to help detect breast cancer, and in lung cancer screening to help identify suspicious nodules.

Additionally, Image segmentation refers to the process of separating an image into different regions or structures. AI algorithms can be used to segment medical images, which can help healthcare providers to identify and diagnose conditions such as tumors or lesions. Furthermore, Radiomics is a field of study that uses AI algorithms to extract quantitative features from medical images. Radiomics can be used to identify biomarkers and patterns in medical images that may be associated with certain diseases or conditions.

Overall, AI has the potential to transform medical imaging in Canada by improving efficiency and accuracy, leading to improved patient outcomes. As technology continues to evolve, it is likely that we will see even more AI-based solutions in medical imaging in the future. Hence Canada AI in the medical imaging market will grow in the coming years.

canada AI in medical imaging market

Market Dynamics

Market Growth Drivers

Growing demand for medical imaging: The demand for medical imaging is increasing due to the aging population, which is driving demand for healthcare services. AI-based medical imaging can help to improve the efficiency and accuracy of medical imaging, which can help to address this growing demand.
Technological advancements: Advances in AI and machine learning algorithms are making it possible to develop more accurate and efficient medical imaging software. This is driving the adoption of AI-based medical imaging solutions in Canada.
Potential cost savings: AI-based medical imaging has the potential to reduce the cost of healthcare by improving efficiency and reducing the need for costly interventions.
Improved patient outcomes: AI-based medical imaging has the potential to improve patient outcomes by facilitating faster and more accurate diagnoses, leading to better treatment options.

Market restraints:

Regulatory hurdles: As noted in my previous response, AI-based medical imaging software is subject to strict regulatory requirements in Canada. These requirements can be a barrier to entry for smaller companies, which may not have the resources to meet these requirements.
Lack of standardization: There is currently a lack of standardization in the development and implementation of AI-based medical imaging solutions. This can make it difficult to compare the effectiveness of different solutions and can create uncertainty around the use of these solutions.
Data privacy and security concerns: The use of AI in medical imaging raises concerns about data privacy and security. Patients may be reluctant to share their medical data, and there are concerns about the potential for data breaches or misuse of patient data.
Impact on jobs: The implementation of AI-based medical imaging solutions could potentially lead to job losses in the healthcare industry. This could create a barrier to adoption for some healthcare providers, and could also create societal concerns around the impact of technology on employment.

Competitive Landscape

Key Players

Imagia (Montreal, Quebec)
Intelerad Medical Systems (Montreal, Quebec)
1QBit - Vancouver, (British Columbia)
Aifred Health (Montreal, Quebec)
HeartForce Medical (Toronto, Ontario)
Swift Medical (Toronto, Ontario)
Resolution Health (Montreal, Quebec)
Hooton AI (Vancouver, British Columbia)
Curate Health (Montreal, Quebec)
Nureca (Vancouver, British Columbia)
Prognica Labs (Mississauga, Ontario)
ScreenPoint Medical (Toronto, Ontario)
Emtec (Toronto, Ontario)
Softnautics (Edmonton, Alberta)
Nanovista - Quebec City, Quebec
Brainomix (Montreal, Quebec)
MaxQ AI (Toronto, Ontario)
Pathcore (Toronto, Ontario)
MIMOSA Diagnostics (Toronto, Ontario)
Retinad (Montreal, Quebec)

Recent Developments

March 2021: The Canadian government announced an investment of $6.8 Mn to support the development and deployment of AI in healthcare, including medical imaging.

September 2020: Imagia, a Montreal-based company, announced the launch of its EVIDENS platform, an AI-powered medical imaging solution that can help identify and predict disease progression.

August 2020: The University Health Network in Toronto announced a partnership with Zebra Medical Vision, an Israeli company that has developed an AI-powered medical imaging analysis platform, to deploy its solution across the network's medical imaging operations.

June 2020: The University of Toronto's Department of Medical Imaging launched an AI research initiative, the Medical Imaging Artificial Intelligence (MI-AI) program, to accelerate the development and adoption of AI in medical imaging.

Healthcare Policies and Regulatory Landscape

The use of artificial intelligence (AI) in medical imaging is regulated by Health Canada, which is the federal regulatory agency responsible for ensuring the safety and efficacy of medical devices and drugs in Canada. Health Canada oversees the approval and regulation of AI-based medical imaging software in Canada.

In 2019, Health Canada released draft guidance for the regulation of AI-based medical devices, including medical imaging software. The guidance outlines the regulatory requirements that manufacturers must meet to obtain approval for their AI-based medical devices, including requirements related to safety, performance, and effectiveness. Under Health Canada's regulatory framework, AI-based medical imaging software is classified as a Class III medical device, which means that it is subject to the highest level of regulatory scrutiny. Manufacturers of AI-based medical imaging software must submit evidence demonstrating the safety, effectiveness, and performance of their products before they can be approved for use in Canada.

Health Canada also requires manufacturers to implement a quality management system (QMS) to ensure that their products meet the regulatory requirements and that they continue to be safe and effective over time. Manufacturers must also monitor their products for adverse events and report any issues to Health Canada. The regulation of AI in medical imaging in Canada is overseen by Health Canada, and manufacturers must meet strict regulatory requirements to obtain approval for their products. The regulatory framework is designed to ensure the safety, efficacy, and performance of AI-based medical imaging software, and to protect the health and well-being of Canadians.

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 surplAustralia 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.