AI in Medical Imaging to Reach USD 1.5 Billion by 2024

These are the latest findings of Signify Research (Cranfield, UK), an independent supplier of market intelligence and consultancy to the global healthcare technology industry.

In 2019, 86% of the world market for AI-based clinical applications for medical imaging was accounted for by four clinical specialties (in order of market size): cardiology, neurology, breast, and pulmonology. Cardiology is forecasted to enjoy the largest revenue growth, followed by pulmonology, and these four clinical segments are projected to still account for more than 75% of the market in 2024. However, new product introductions of AI solutions for other clinical segments, most notably prostate and liver imaging, are on the rise.

Until now, the growth of the global market for AI-based clinical applications for use in medical imaging has been less rapid than anticipated by several industry experts due to several technical and commercial barriers, and a further set back dealt by the COVID-19 global pandemic. These barriers to market adoption, including the utility of AI in clinical practice, lack of clinical validation, challenges of workflow integration, and limited reimbursement, must be fully addressed before the use of AI in radiology becomes mainstream.

“The market is highly dynamic and continues to evolve at a rapid pace, said Dr. Sanjay Parekh. Senior Analyst at Signify Research. “There are frequent product launches, and the availability of regulatory approved products is accelerating. Since 2018, almost 60 AI-based clinical applications for medical imaging have received US-FDA approval, while a similar number of solutions have received CE Mark approval.”

Despite the many challenges of bringing medical imaging AI solutions to market, "radiology AI is here to stay," added Dr. Parekh. "From enhanced productivity and increased diagnostic accuracy, to more personalized treatment planning and improved clinical outcomes, AI will play a key role in enabling radiologists to meet the demands of their workload. The increasing volume of diagnostic imaging procedures, exacerbated by the current backlog of imaging exams due to national lockdowns, coupled with the shortage of radiologists in many countries, will undoubtedly further increase the need for AI in radiology."

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