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Artificial Intelligence (AI) in MRI Market - Forecasts from 2023 to 2028

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  • 124 Pages
  • May 2023
  • Region: Global
  • Knowledge Sourcing Intelligence LLP
  • ID: 5794092

The artificial intelligence in MRI market is projected to grow at a CAGR of 35.7% to reach US$1,539.622 million in 2028 from US$181.720 million in 2021.

Artificial Intelligence (AI) is increasingly used in Magnetic Resonance Imaging (MRI) to improve image quality, enhance diagnostic accuracy, and reduce the time required for analysis. AI algorithms can process and analyze large amounts of imaging data in a fraction of the time it would take a human expert. In addition, AI algorithms can segment anatomical structures in MRI images, such as the brain, liver, or heart. This can be useful for planning surgeries or radiation therapy.

Furthermore, MRI images can be noisy, reducing their quality and accuracy. AI algorithms can remove noise from MRI images, improving their diagnostic value. AI algorithms can also register or align multiple MRI images of the same patient at different times or angles. This is useful for tracking disease progression or response to treatment. They can also classify MRI images into different categories, such as normal or abnormal, or differentiate between different types of abnormalities. This can aid in diagnosis and treatment planning and be used for predictive modeling. For example, they can predict the likelihood of a patient developing Alzheimer's disease based on MRI images of their brain.

The artificial intelligence in MRI market is driven by growing demand for imaging services and cloud healthcare solutions due to rising cases of chronic ailments and government ventures. Governments worldwide are investing in healthcare infrastructure and technology to improve patient outcomes and reduce costs. This includes investments in AI technologies for MRI, which can help to improve access to imaging services and reduce wait times.

Further, the increasing prevalence of chronic diseases and the aging population have led to a growing demand for medical imaging services, including MRI. AI algorithms can help healthcare providers to provide more accurate and efficient diagnostic services, reducing wait times and improving patient outcomes. According to the US National Institutes of Health (NIH), the demand for medical imaging services is growing rapidly, with MRI being one of the most used modalities. The NIH reports that the number of MRI exams performed in the US increased from 10.5 million in 2000 to 42 million in 2017.

The increasing adoption of cloud-based solutions for medical imaging is also driving the growth of the AI in MRI market.

Cloud-based solutions enable healthcare providers to access and share imaging data more easily, improving collaboration and patient outcomes. The US Department of Health and Human Services (HHS) launched a new initiative called the "MyHealthEData" initiative in 2018, which aims to promote the adoption of cloud-based solutions for medical imaging and other healthcare services.

Market Developments:

In November 2022, GE Healthcare unveiled a new artificial intelligence platform called SIGNA to streamline much of the legwork involved in MRI scanning, using software for technologists with little expertise. The SIGNA Experience helps staff prepare the company's SIGNA scanners and obtain clear diagnostic images as quickly as possible by combining AI- and deep learning-powered applications with simple-to-position magnetic coils. The service is centered on SIGNA One, a simpler computer interface available on GE's smaller, 1.5T SIGNA Prime scanner, and was developed to increase the adoption of MR imaging in emerging economies outside of the United States. It can extract more signal data from quicker scans and various imaging methods.

In November 2021, Philips, a major firm in health technology, unveiled significant advancements in MR imaging that are enabled by AI. The MR range of intelligent integrated solutions from Philips can accelerate MR exams, streamline workflows, improve diagnostic accuracy, and support the sustainability and efficiency of radiology operations. The company's MR Workspace with AI assistance, which offers an intuitive solution to simplify the path from image acquisition to diagnosis to help improve MR workflow and staff experience, and Philips SmartSpeed, designed to speed up image acquisition and enhance image quality and diagnostic confidence for every patient, were two of the new AI-enhanced MR innovations Philips introduced in 2021. In addition, the business also unveiled its new MR 5300 and MR 7700 smart connected systems in the same period.

Based on end-users, the artificial intelligence in MRI market is expected to witness positive growth in the hospital segment.

Hospitals are expected to be the major end-users of AI in MRI, owing to their ability to invest in expensive medical equipment and advanced technologies. In addition, hospitals have large patient volumes, which creates a need for faster and more accurate diagnoses. AI in MRI can help hospitals to reduce the workload on radiologists, increase diagnostic accuracy, and improve patient outcomes.

North America and Europe account for the major share of artificial intelligence in MRI market.

Based on geography, the artificial intelligence in MRI market is analyzed into North America, South America, Europe, Middle East and Africa, and Asia Pacific regions.

North America is expected to hold a significant proportion of the AI in MRI market, owing to well-established healthcare infrastructure, advanced medical technologies, and government support for research and development of AI technologies. As a result, the US is the largest market for AI in MRI in North America.

Europe is also expected to hold sizable shares of the AI in MRI market, owing to the increasing adoption of AI technologies in healthcare and growing government initiatives for healthcare IT development. The European Union has invested US$2.5 billion in the development of AI technologies as part of its Digital Single Market strategy. The UK, Germany, and France are the major markets for AI in MRI in Europe.

Market Segmentation:

By Solution

  • Software
  • Services

By End-User

  • Hospitals
  • Clinics
  • Diagnostic Centers

By Geography

  • North America
  • USA
  • Canada
  • Mexico
  • South America
  • Brazil
  • Argentina
  • Others
  • Europe
  • United Kingdom
  • Germany
  • France
  • Italy
  • Spain
  • Others
  • Middle East and Africa
  • Saudi Arabia
  • UAE
  • Others
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Singapore
  • Indonesia
  • Others

Table of Contents

1.1. Market Overview
1.2. Market Definition
1.3. Scope of the Study
1.4. Market Segmentation
1.5. Currency
1.6. Assumptions
1.7. Base and Forecast Years Timeline
2.1. Research Data
2.2. Research Design
2.3. Validation
3.1. Research Highlights
4.1. Market Drivers
4.2. Market Restraints
4.3. Porter’s Five Forces Analysis
4.3.1. Bargaining Power of Suppliers
4.3.2. Bargaining Power of Buyers
4.3.3. Threat of New Entrants
4.3.4. Threat of Substitutes
4.3.5. Competitive Rivalry in the Industry
4.4. Industry Value Chain Analysis
5.1. Introduction
5.2. Software
5.3. Services
6.1. Introduction
6.2. Hospitals
6.3. Clinics
6.4. Diagnostic Centers
7.1. Introduction
7.2. North America
7.2.1. USA
7.2.2. Canada
7.2.3. Mexico
7.3. South America
7.3.1. Brazil
7.3.2. Argentina
7.3.3. Others
7.4. Europe
7.4.1. United Kingdom
7.4.2. Germany
7.4.3. France
7.4.4. Italy
7.4.5. Spain
7.4.6. Others
7.5. Middle East and Africa
7.5.1. Saudi Arabia
7.5.2. UAE
7.5.3. Others
7.6. Asia Pacific
7.6.1. China
7.6.2. Japan
7.6.3. India
7.6.4. South Korea
7.6.5. Australia
7.6.6. Singapore
7.6.7. Indonesia
7.6.8. Others
8.1. Major Players and Strategy Analysis
8.2. Emerging Players and Market Lucrativeness
8.3. Mergers, Acquisition, Agreements, and Collaborations
8.4. Vendor Competitiveness Matrix
9.1. Siemens Healthineers AG
9.2. GE HealthCare
9.3. IBM
9.4. Philips Healthcare
9.5. NVIDIA Corporation
9.6. Oxipit.ai
9.7. Quibim
*Not an exhaustive list

Companies Mentioned

  • Siemens Healthineers AG
  • GE HealthCare
  • IBM
  • Philips Healthcare
  • NVIDIA Corporation
  • Oxipit.ai
  • Quibim



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