The global artificial intelligence in magnetic imaging (MRI) market size was estimated at USD 5.77 billion in 2022 and is expected to hit around USD 10.8 billion by 2032 with a registered CAGR of 6.23% from 2023 to 2032.
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Artificial intelligence (AI) is the field of study that creates computerized models to perform tasks that normally require human intelligence. Magnetic Resonance Imaging (MRI) is a non-invasive imaging technique that produces three-dimensional anatomical images. It is widely employed in disease detection, diagnosis, and treatment monitoring. It is based on advanced technology that excites and detects changes in the rotational axis of protons in the water that makes up living tissues.
Artificial intelligence (AI) has transformed the medical imaging landscape by improving diagnostic accuracy and treatment planning for healthcare professionals. The advancement of technology has paved the way for disease diagnosis and medical image evaluation. Machine learning (ML) integration has also improved clinical outcomes and next-generation diagnostic methods. The introduction of new AI software and the use of such tools in routine diagnosis will result in more accurate clinical outcomes. Artificial intelligence (AI) has become a vital feature of many radiology subspecialties, particularly neuroradiology, which relies heavily on magnetic resonance imaging (MRI) to help diagnose conditions affecting the central nervous system. AI-powered solutions provide accurate volumetric measurements to assist in determining how much healthy brain tissue may be spared from damage, and then automatically fill that data into dictation platforms and other systems. Artificial intelligence (AI) for medical imaging is an efficient strategy. An in-depth grasp of the fundamentals and applications of magnetic resonance imaging (MRI), machine learning (ML), and deep learning (DL) is required for designing AI-based algorithms that can match clinical diagnosis requirements while also being of high quality and efficiency.
As the number of COVID-19 cases increases worldwide, new AI technologies are being developed to assist hospitals in expanding their second-wave treatment. Through remote access to images and reports, the COVID-19 pandemic has increased corporate image processing and telemedicine demand. It also emphasizes the significance of expanding the use of AI and machine learning in diagnostic imaging, with two goals in mind: improving diagnostics and clinician well-being, and job safety. Scientists have made significant contributions to the fight against COVID-19. The number of research results, such as analytical reports and publications, reported by both industrial and academic researchers is growing daily.
AI has demonstrated incredible accuracy and sensitivity in the classification of image anomalies in recent years, improving tissue-based detection and characterization. The incorporation of artificial intelligence (AI) into healthcare and medical imaging has changed the nature of diagnostics and contributed to the growth of global AI in medical imaging market. Artificial intelligence assists doctors in performing imaging procedures and in diagnosing and treating patients individually. Researchers use AI to recognize complex patterns in image data and quantitatively evaluate radiograph characteristics.
Increased chronic infections with an increasing number of disorders among individuals with enhanced diagnostics methods developed in the market with new incorporate into the system with increased output and good performance and high precision increased the market of artificial intelligence in the MRI market with growing demands from the health care sector with faster results and quick treatment for the patient outperforms industry growth to a greater extent.
The shortage of trained professionals who are unable to use these techniques is the factor that limits the growth of the artificial intelligence-based magnetic resonance imaging (MRI) industry.
Furthermore, the massive investment required to set up or develop the techniques will thwart future growth. Several market players make large investments in installing new and advanced machines to speed up the process, which raises the cost.
Several major AI players in the medical imaging industry are starting to collaborate or partner with leading AI technology providers to develop AI-based solutions for healthcare applications. With this approach, market participants can provide advanced solutions to consumers while also establishing their position in this volatile market environment. As the demand for AI-based technologies grows, advancements can provide enterprises with a boost in developing advanced products and tools. However, AI technology is expected to have a significant impact in a few areas. These include enhanced diagnostics and unintentional image discoveries, predictive image analysis, workflow efficiency with data analysis, and reporting and prioritization of critical discoveries.
Developing countries are focusing on increasing their AI investments, which will assist companies in integrating AI with medical imaging to increase their revenue share. For instance, China aims to be the global leader in AI by 2030. The strategy entails significant government funding and investments to increase the adoption of AI solutions in industries. Furthermore, rising patient populations in countries such as India, China, and Brazil are expected to provide significant growth opportunities for players in the AI-based MRI industry.
The medical sector is looking for innovative tools to monitor and control the spread of the COVID-19 (Coronavirus) pandemic in this global health disaster. AI is one such technology that easily follows the transmission of this virus, identifies high-risk patients, and aids in real-time infection management. It can also forecast mortality risk by thoroughly evaluating the patients' historical data. AI assists in combating the virus through population screening, medical assistance, notification, and infection control recommendations. AI rapidly evaluate unusual symptoms and other "red flags," alerting patients and healthcare providers. It contributes to faster and more cost-effective decision-making. Effective algorithms contribute to the development of a new diagnosis and management strategy for COVID-19 cases. AI aids in the diagnosis of infected patients by utilizing medical imaging technologies such as computed tomography (CT) and magnetic resonance imaging (MRI) scans of human body parts. AI assists in analyzing the level of infection by this virus, locating clusters and 'hot spots,' as well as successfully tracing and monitoring individuals. It forecast the disease's future course and the likelihood of recurrence. This technology tracks and forecasts the virus's characteristics based on accessible data, social media, and media channels, as well as the risks of infection and its potential propagation. It also forecasts the number of positive cases and deaths in any region.
AI assists in identifying the most susceptible places, people, and countries and taking appropriate measures. Healthcare professionals are working extremely hard due to a sudden and significant surge in the number of patients during the COVID-19 pandemic. In this case, AI is being used to lower the workload of healthcare professionals. It aids in early diagnosis and treatment by utilizing digital techniques and decision science, and it provides the best training to students and professionals regarding this new disease. AI can improve future patient care and address more possible difficulties, reducing doctors' burden. The outbreak of covid-19 with the wide spread of coronavirus in various regions increased hospitalization of patients with increased technology for disorder diagnosis which fuels the growth of artificial intelligence in MRI and in the post-pandemic situation with increased consumer demands in the medical sector with enhanced connectivity and software structure with increased features in MRI scanning with fast detection of the problem and quick treatment Increased research and development with enhanced technology and procedures in MRI aids in market expansion.
The AI in the MRI industry is segmented based on clinical applications, offering type, technology, deployment type, and end-user. Based on clinical application, the industry is further segmented into musculoskeletal, colon, prostate, liver, cardiovascular, neurology, lung, breast, and others. Based on offering type it is further segmented into Hardware, Software, and Services. Based on technology, the Ai in the MRI industry is segmented further into deep learning, machine learning, computer vision, NPP (natural language processing), speech recognition, querying method, and others. Based on the deployment type, the industry is further segmented into on-premise and cloud. Based on end-user, Ai in the MRI industry is further segmented into hospitals, clinics, research and laboratories, and others.
Improve artificial intelligence applications in MRI in the medical industry with growing chronic disorders. Artificial intelligence in MRI is widely used in neurology with the highest industry share due to enhanced therapies for the brain with advances in the treatment and technology with integrated software into the computer with enhanced efficiency for scanning images with easy recognition of the circumstances and also widely used in cardiovascular due to increasing heart problems in day to day life with increased lifestyle changes and intake of dietary supplements which affects the health As a result, the artificial intelligence industry is expected to expand throughout the forecast period.
AI in MRI Market Share, Deployment Type, 2022 (%)
| Segments | Revenue Share in 2022 (%) |
| On-Premise | 60% |
| Cloud | 40% |
Artificial intelligence in MRI based on deployment type and enhanced network technology aids market expansion. Increased integration of clouding systems and easy data transmission with improved connectivity and easy management of work and increased performance in various sectors increased the Internet of Things continually and market expansion to expand.
Based on end-user, Ai in the MRI industry is further segmented into hospitals, clinics, research and laboratories, and others. With greater advancements in technologies and advances with more features and chronic diseases, industry growth has outpaced market growth with higher demands from the healthcare care sector for developed artificial intelligence in MRI. Hospitals with a higher market rate and a higher rate of hospitalization for serious disorders aid in imaging and scanning with faster treatment and enhanced advancements and software systems integrated into medical scanning devices and computers. This enables the market to expand.
North America holds the major industry share owing to the increased revenue due to developed technology and advancements in artificial intelligence in MRI with increased performance and good results help the healthcare center with rapid diagnosis and quick treatment involved for patients with rising disorders.
Given the increasing number of government initiatives to promote healthcare providers, Asia-Pacific is predicted to be the fastest-growing region in terms of development in the artificial intelligence-based MRI Industry
Partnerships, acquisitions, mergers, collaborations, and new product launches with cutting-edge and innovative features stimulate Industry growth and provide attractive growth prospects to market players. Prominent players in the industry are IBM Corporation, Bay Labs Inc, Resonance Health Ltd, Zebra Medical Vision Inc, Samsung Electronics Co.Ltd, Arterys Inc., Koninklijke Philips N.V., Nuance Communications Inc., Siemens Healthneer AG, OrCam, NVIDIA Corporation, Freenome Holdings Inc., Clarify Health Solutions, BioXcel Therapeutics, GNS Healthcare, Qventus, K Health Inc, Huma, Voxel, OWKIN INC., BERG LLC, Suki Al Inc, Renalytix, Babylon, Aga Health GmbH, Prognos, Medopad Ltd, PAIGE
Deepa has certified the degree of Master’s in Pharmacy in the Pharmaceutical Quality Assurance department from Dr D.Y.Patil College of Pharmacy. Her research is focused on the healthcare industry. She is the author or co-author of four Review Articles, which include Solid dispersion a strategic method for poorly soluble drugs and solubility improvement techniques for poorly soluble drugs, Herbal Drugs Used In Treatment Of Cataracts, Nano sponges And Their Application in Cancer Prevention and Ayurvedic Remedies of Peptic ulcer. She has also published a Research Article on the Formulation and Evaluation of Mucoadhesive Tablets of Miconazole cocrystal which was published in GIS Science Journal Volume 9 Issue 8. Her passion for secondary research and desire to take on the challenge of solving unresolved issues is making her flourish is the in the research sector.
