Author: Acumen Research and Consulting

The global AI in Medical Imaging Market size occupied USD 1.4 Billion in 2022 and is projected to achieve a size of around USD 23.7 Billion by 2032 rising with a CAGR of 33.6% during the forecasted years, as reported by Acumen Research & Consulting

The AI in medical imaging business is now in great demand and is expected to increase significantly in the next years. AI technology integration in medical imaging has the potential to transform healthcare by boosting diagnosis accuracy, increasing workflow efficiency, and allowing personalized patient care.

The requirement for precise and rapid diagnosis is one of the key drivers of demand in the business. For successful treatment planning and improved patient outcomes, accurate and fast diagnosis is critical. Radiologists and physicians can benefit from AI algorithms that analyze medical pictures, identify problems, and provide precise diagnostic insights. AI in medical imaging can dramatically enhance diagnostic accuracy and efficiency by automating mundane operations and enhancing human knowledge.

Moreover, the rising frequency of illnesses, particularly chronic ones like cancer, cardiovascular disease, and neurological disorders, has spurred demand for AI in medical imaging. Medical imaging is critical in detecting and monitoring these disorders. AI algorithms can improve imaging modalities' capabilities by automating processing and offering better picture interpretation, allowing for early detection and accurate diagnosis.

Advances in imaging technology and data management systems are also driving the sector. Continuous advancements in imaging modalities such as CT, MRI, and ultrasound, as well as increased data storage and processing capabilities have made it possible to generate high-quality medical pictures. These breakthroughs may be used by AI systems to extract significant information from photos and deliver precise diagnostic findings.

AI in Medical Imaging Market Statistics

• Global AI in medical imaging market revenue accounted for USD 1.4 billion in 2022, with a 33.6% CAGR from 2023 to 2032
• North American AI in medical imaging market share occupied around 44% in 2022
• Asia-Pacific AI in medical imaging market growth is projected to attain over 34% CAGR from 2023 to 2032
• By technology, the deep learning sub-segment grabbed over 58% share in 2022
• Among end-user, the hospitals sub-segment gathered over USD 707 million in revenue in 2022
• The application of AI in image-guided interventions and surgical planning is a recent AI in medical imaging market trend

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AI in Medical Imaging Market Dynamics

Rising Adoption of Electronic Health Records (EHR) and Integration of AI Systems Drives the Artificial Intelligence in Medical Imaging Market Value

The increasing use of electronic health records (EHR) and the integration of AI systems have been important demand drivers in the AI medical imaging business.

Electronic health records (EHR) have become widely used in healthcare systems, allowing for the digitalization and centralized storage of patient health data. Medical imaging, patient demographics, medical history, and clinical notes are all stored in EHR systems. This information is useful for training AI systems in medical imaging.

Healthcare practitioners may use a large quantity of patient data to train AI algorithms and construct models for image analysis and interpretation by connecting AI systems with EHR platforms. This integration enables radiologists and clinicians to make more informed and accurate diagnoses by providing continuous access to patient information during the image processing process.

AI integration with EHR also improves process efficiency. AI algorithms may help with regular activities including image pre-processing, lesion identification, and segmentation. AI minimizes the time and effort required for radiologists and doctors by simplifying these processes, allowing them to focus more on difficult situations and patient care.

Furthermore, integrating AI systems with EHR offers decision assistance features. Artificial intelligence systems can analyze medical pictures in real-time and give valuable clinical insights, assisting radiologists and doctors in making correct and timely judgments. This decision help might involve recommending potential diagnoses, flagging areas of concern, and advising suitable next steps.

Application of AI in Image-Guided Interventions and Surgical Planning Will Generate Surplus AI in Medical Imaging Market Opportunities

Another key element boosting demand in the AI medical imaging business is the use of AI in image-guided interventions and surgical planning. Image-guided interventions use real-time imaging tools like ultrasound, CT, or MRI to guide minimally invasive treatments or operations. AI algorithms have the potential to significantly improve the precision and effectiveness of these therapies. AI algorithms can aid in the proper targeting of the treatment region by analyzing real-time imaging data and offering recommendations to healthcare personnel during treatments. In interventional radiology operations, for example, AI can assist in identifying and tracking the position of blood arteries or tumors, allowing for more precise catheter insertion or needle biopsy.

AI may analyze preoperative imaging data, such as CT scans or MRI, to aid surgeons in creating surgical strategies during surgery planning. Anatomical structures may be segmented, regions of interest identified, and probable surgical outcomes simulated using AI algorithms. This data can help surgeons determine the best technique, analyze risks, and improve surgical accuracy.

By combining real-time images with surgical equipment, AI can also aid in surgical navigation. AI algorithms can give feedback and advice to surgeons throughout the surgery by tracking the location of tools relative to the patient's anatomy, assuring correct placement and lowering the chance of problems.

The use of artificial intelligence in image-guided treatments and surgical planning has the potential to increase procedure accuracy, decrease operating time, reduce invasiveness, and improve patient outcomes. As a result, there is an increasing demand for artificial intelligence (AI) solutions that can give real-time analysis and advice throughout these operations.

AI in Medical Imaging Market Segmentation

The global market has been categorized into technology, modality, application, end-user, and region.

• The technology segment covers deep learning, natural language processing (NLP), and others
• Modality segment includes CT scans, MRI, ultrasound, nuclear imaging, and X-rays
• The application segment is categorized into breast screening, cardiology, neurology, orthopedics, respiratory and pulmonary, and others
• The end-user segment is split into hospitals, diagnostic imaging centers, and others
• The market is divided into five regions that are North America, Europe, Latin America, Asia-Pacific, and The Middle East and Africa (MEA)

AI in Medical Imaging Market Share

Deep learning technology held a sizable market share in 2022, and natural language processing (NLP) is anticipated to grow at a significant rate in the next years.

In 2022, the CT scan modality led AI in the medical imaging market and is projected to do so in the future.

According to the AI in Medical Imaging industry analysis, the neurology application sub-segment will have the most market share in 2022. Between 2023 and 2032, the application of cardiology is predicted to rise significantly.

According to AI in medical imaging market forecasts, the hospitals sub-segment will account for a large portion of the market between 2023 and 2032. In contrast, academic/research institutes are likely to prosper in the next few years.

AI in Medical Imaging Market Regional Outlook

North America, notably the United States, has been a market leader in AI in medical imaging. The area benefits from modern healthcare infrastructure, a strong R&D environment, and the presence of key market participants. The rising acceptance of AI technology in medical imaging, favorable government efforts, and significant investment in R&D all contribute to the region's market growth.

Europe is another important market for artificial intelligence in medical imaging. Germany, the United Kingdom, France, and the Netherlands have all made significant expenditures in healthcare technology and research. The region boasts well-established healthcare systems, cutting-edge imaging facilities, and a favorable regulatory climate. The growing need for efficient and accurate diagnostic tools, as well as the necessity to manage the growing burden of chronic illnesses, is driving the development of AI in medical imaging.

The AI in medical imaging industry is rapidly expanding in the Asia Pacific region. Countries such as China, Japan, South Korea, and India are investing heavily in healthcare infrastructure and using AI technology. The region has a huge population, a rising prevalence of chronic illnesses, and a growing understanding of the benefits of AI in healthcare. These elements, together with government measures to encourage digital healthcare and improvements in medical imaging technology, all contribute to the region's market growth.

AI in Medical Imaging Market Players

Some prominent AI in Medical Imaging companies covered in the industry includes IBM Watson Health, GE Healthcare, Siemens Healthineers, Philips Healthcare, NVIDIA Corporation, Aidoc, Butterfly Network, Zebra Medical Vision, Arterys, Hologic, Inc., Samsung Healthcare, Fujifilm Holdings Corporation, Agfa-Gevaert Group, iCAD, Inc., and MIRADA Medical Ltd.

AI in Medical Imaging Industry Player Strategies

In April 2022, NVIDIA unveiled the Clara AGX, an artificial intelligence-powered platform for medical imaging and genomics. The Clara AGX platform is intended to speed up AI inference and training workloads in medical imaging applications, allowing healthcare providers and researchers to create and deploy sophisticated AI models.

In November 2021, Philips Healthcare established a partnership with artificial intelligence software vendor Lunit to incorporate Lunit's AI-powered tools into Philips' radiology products. The collaboration intends to improve Philips imaging equipment's diagnostic capabilities by employing Lunit's deep learning algorithms for the detection of various abnormalities and illnesses.

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