The global AI-based medical imaging market size was valued at USD 1,543.77 million in 2022. It is estimated to reach USD 45,062.18 million by 2031, growing at a CAGR of 45.68% during the forecast period (2023–2031).
The global AI-based medical imaging market's healthy expansion is attributable to the surge in the adoption of AI in major areas of medical imaging specialties and modalities worldwide. The market is experiencing exceptional topline growth due to the rise in awareness of advanced imaging technologies among radiologists to ease their workload with enhanced images, increased sensitivity, and accuracy.
AI-based medical imaging involves using AI in diagnostic medical imaging to detect abnormalities based on changes in imaging intensities or the appearance of unfamiliar patterns. The deployment of AI-based medical imaging solutions across all imaging modalities and specialties facilitates the processing and interpretation of images. AI-based medical imaging solutions are currently available as software tools or platforms for accurate and accessible disease screening and desired image clarity in less time, enhancing radiologists' workflow and productivity.
Traditional imaging techniques have difficulty detecting patient condition changes in real-time. In medical imaging, AI and machine learning technologies are advantageous for monitoring the patient's condition and detecting the slightest change in vast amounts of data. This is an effective method for monitoring brain tumors and other cancers and is crucial for determining the optimal treatment. For example, standard medical imaging cannot ascertain the proportion of living or dead tumor cells.
|Market Size||USD 45,062.18 million by 2031|
|Fastest Growing Market||Europe|
|Largest Market||North America|
|Report Coverage||Revenue Forecast, Competitive Landscape, Growth Factors, Environment & Regulatory Landscape and Trends|
Under the current regulatory framework, there is a noticeable acceleration of FDA approvals for AI-assisted medical imaging diagnostics. Currently, the Food and Drug Administration (FDA) has granted clearance to a minimum of 16 applications that utilize artificial intelligence (AI) technology. The number of approved AI-based devices has increased since 2015, with many being approved for use in radiology.
For instance, in May 2019, the FDA approved Zebra Medical Vision's HealthPNX for utilization in radiology. Similarly, in April 202, Canon Medical Systems, a global leader in innovative diagnostic imaging technology, received approval for the CT scan product Cartesian Prime. Thus, the rise in FDA approvals for AI-based medical imaging products is expected to drive market growth during the forecast period.
The demand for all aspects of diagnostic procedures is increasing every year. The increase in the demand has been driven partly by an increase in imaging activity across many aspects of acute hospital activity, with a particular surge in demand from urgent referrals for cancer (10% per year) imaging. Wider indications for tests such as CT scanning fuel the demand for medical imaging.
Additionally, the surge in the prevalence of cardiac and respiratory diseases has accelerated the demand for diagnostic solutions. GE Healthcare has claimed that over 90% of healthcare data is sourced from medical images, out of which more than 97% are not analyzed. Thus, with the surge in diagnostic procedures, AI-assisted medical imaging has helped improve workflow and efficiency, accelerating the demand for AI-based medical imaging diagnostics.
Most resource-poor health institutions, particularly in low-and middle-income countries, do not have a digital infrastructure to support their healthcare systems. Two-thirds of countries worldwide lack or have insufficient radiology facilities. In low- and middle-income nations, the lack of skilled radiologists has emerged as a barrier to adopting AI-based medical imaging diagnostics. For instance, Tanzania has only 60 radiologists for 58 million people, a 50-fold deficit compared to the per capita US radiologist population. Such factors restrict market growth.
AI-based medical imaging devices are increasingly being adopted in developed countries across North America and Europe. The surge in the adoption of AI-based medical imaging devices is also attributable to the rise in approval from regulatory bodies in developed countries. The number of approved AI-based medical imaging devices has increased since 2015, with many being approved for use in radiology. In the US, imaging centers have reported a slightly higher adoption rate of AI technology than hospitals.
In 2019, it was projected that approximately 53% of healthcare professionals planned to use AI-based medical imaging in the upcoming years. In 2019, approximately 250,000 radiologists were performing diagnostic imaging examinations on patients in the US alone. In addition, the US Bureau of Labor Statistics indicated that from 2019 to 2029, the number of radiologists is estimated to develop by 7%, faster than the average for all professions. Therefore, the intensifying work pressure has compelled radiologists to adopt AI-based tools to automate some of their tasks and meet the surge in demand for medical imaging services, thereby creating opportunities for market growth.
Based on region, the global AI-based medical imaging market is bifurcated into North America, Europe, Asia-Pacific, Latin America, and the Middle East and Africa.
North America is the most significant global AI-based medical imaging market shareholder and is estimated to exhibit a CAGR of 45.12% during the forecast period. In North America, the adoption rate of AI-based medical imaging solutions is high due to the surge in investments by large companies, public and private entities, the rise in partnerships and collaborations among vendors, and the role of research institutes in the development of AI-based medical imaging, and the increase in reimbursements to hospitals. Therefore, many radiologists and hospitals in the US prefer AI-based medical imaging software/applications.
In addition, the high adoption of AI-based medical imaging solutions in the US is also due to a well-established healthcare system, which includes a reimbursement policy. The high involvement of healthcare payers is also driving the growth of the US AI-based medical imaging market. For instance, Medicare established a New Technology Add-on Payment (NTAP) in the Inpatient Prospective Payment System (IPPS) for Viz.ai company's Viz LVO.
Europe is expected to exhibit a CAGR of 43.93% over the forecast period. The regional market is growing at a healthy rate and is expected to grow similarly during the forecast period. AI-based medical imaging solutions can enable the region to transform its medical domain. In the last two years, the European region witnessed a spike in collaborative research between companies, research centers, hospitals, and many more to develop AI-based medical imaging tools. This research has also received extensive funding from various governments. However, several start-ups have introduced a wide range of AI-based medical imaging tools/software with deep learning technology with high funds from the government. Large established companies have also made considerable investments in collaborative research with research and academic institutions, hospitals, and research organizations to grow in this market.
Asia-Pacific is the third-largest market for AI-based medical imaging solutions. The adoption rate of advanced AI technologies in the medical imaging sector is still emerging in this region. China and Japan are the leading nations in adopting AI-based medical imaging software and tools in this region. In recent years, there has been a noticeable surge in investment by government and corporations, as well as collaborations and partnerships among companies,
research centers, and institutes, which shows that there could be exponential growth in the market during the forecast period. Due to these factors, the market is expected to witness exponential growth. However, some limitations include the high costs of adopting AI systems in medical imaging. These sophisticated systems require a large budget that could hamper the growth of the AI-based medical imaging market in Asia-Pacific, including the high cost of AI technologies and the lack of well-organized, reliable, and cybersafe IT environments.
In Latin America, factors such as the rapidly increasing population, growing demand for medical imaging, increasing healthcare expenditure, and the rising number of diagnostic imaging service providers are driving the market's growth. In Latin America, there are tremendous opportunities for adopting AI-based medical imaging. Many newly launched AI research centers perform AI-based medical imaging research in partnership with vendors. For instance, the Sao Paulo Research Foundation (FAPESP), a public foundation that supports research projects in higher education and research institutions in Brazil, has partnered with IBM to launch the first Latin American institution of IBM's AI Horizons Network. The research laboratory will receive substantial investment from funding agencies and academic organizations in the next ten years.
Turkey, Saudi Arabia, South Africa, and the UAE are prominent revenue contributors to the regional market. The growing burden of non-communicable diseases and other prevalent diseases is causing a health crisis in the region. The increasing pressure to reduce healthcare costs while addressing chronic diseases is emerging as a serious challenge for governments and health agencies in the region. Although radiological exams are not expensive in countries such as Turkey, the high exposure of patients to radiation doses makes them prone to cancer. It contributes to the surge in healthcare costs. Such factors have accelerated the region's adoption rate of AI-based medical imaging solutions.
The global AI-based medical imaging market is bifurcated into technology, application, modalities, and end-user.
Based on technology, the global AI-based medical imaging market is bifurcated into deep learning, natural language processing, and others.
The deep learning segment is the highest contributor to the market and is anticipated to exhibit a CAGR of 47.04% over the forecast period. Deep learning is a sub-segment of machine learning. It generally has two properties, i.e., multiple processing layers that can learn distinct data features through multiple levels of abstraction and unsupervised or supervised learning of feature presentations on each layer. Deep learning is applicable for detecting abnormalities and classifying a specific type of disease. In addition, deep learning is a new AI machine-learning technique, and its medical applications have generated much interest over the past few years. It is designed to mimic the layers of neurons in the human brain to process and extract information, allowing computers to learn without being explicitly programmed. This technique is being applied or implemented to detect diseases.
Based on application, the global AI-based medical imaging market is segmented into neurology, respiratory and pulmonary, cardiology, breast screening, orthopedics, and others.
The neurology segment is the largest revenue contributor to the market and is projected to exhibit a CAGR of 46.45% over the forecast period. Recently, AI has been increasingly applied in medical imaging, especially molecular imaging of the central nervous system. AI and neuroscience continue to be heavily interdependent, and the increasing application of AI in neuroscience is immensely benefiting the healthcare industry. Most active companies in this area include start-ups that have acquired multiple funding rounds. In addition, many of these companies are from Europe and North America. However, many Asian companies have launched their products in recent years due to the high funding. Therefore, a significant contribution to future AI developments from this continent can be expected. Arterys Neuro AI, a neuro-oncology suite, provides the tools to distinguish tumors from pseudo-progression with >95% accuracy non-invasively.
Based on modalities, the global AI-based medical imaging market is bifurcated into Computed tomography (CT), MRI, X-rays, ultrasound, and nuclear imaging.
The CT segment dominates the global market and is predicted to grow at a CAGR of 46.16% over the forecast period. Computed tomography (CT) has a broad diagnostic application. It is the gold standard of imaging for many clinical indications. However, it has many disadvantages. Exposing patients to higher doses increases cancer risk for all patients,
particularly higher-risk populations, such as pediatric, obese, or oncology patients who require regular screening. In addition, AI-based machine learning technologies in CT imaging can be used to directly manage the dose and quality of the image. AI-based CT imaging can process CT images within seconds with accurate results. Many key and small vendors offer a comprehensive range of AI-based CT imaging diagnostic solutions across North America and Europe.
Based on end-users, the global AI-based medical imaging market is bifurcated into hospitals, diagnostic imaging centers, and others.
The hospitals segment owns the highest market share and is expected to exhibit a CAGR of 44.83% over the forecast period. The incorporation of AI-based medical imaging software/algorithms/systems in hospitals has happened recently. The surge in the prevalence of chronic diseases such as cancer, cardiovascular conditions, neurological diseases, respiratory diseases, and many other medical conditions has increased imaging activities in hospitals. The exponential rise in medical imaging data has increased the work pressure on radiologists and healthcare departments with conventional medical imaging systems.
Likewise, since the COVID-19 outbreak, the number of patient visits to seek medical imaging services increased by more than 200% compared to the pre-pandemic levels, which is attributable to the surge in demand for respiratory imaging in hospitals.