In 2020, the COVID-19 pandemic put an unprecedented load on medical systems worldwide. While the lack of capacity had been felt earlier, the pandemic highlighted a severe deficiency. Developing technological instruments empowering medical staff to treat more patients attracted attention. Moreover, technological advancement and data availability have made the healthcare industry more data-driven and analytical. In contrast, the quality and the speed of data processing have become essential factors in healthcare decision-making. The demand for deeper integration of mathematical algorithms, such as artificial intelligence (AI) and in particular, machine learning (ML) in healthcare became evident. Already in 2020, 69% of medical institutions in the US and Europe started pilot AI projects. The boom in big data analysis tools and the availability of cheap computing power only strengthened this trend.
One specific application of AI in medicine is medical image analysis. Although a relatively narrow market at present, it addresses severe health conditions and diseases like cancer or COVID-19 complications. Moreover, AI/ML has the potential to revolutionize clinical studies by enabling researchers to extract insights from large and complex datasets more efficiently and accurately than traditional statistical methods.
Advances in computer vision technology have made imagery-based technology accurate and reliable enough for practical healthcare applications. It was already accepted as an essential tool in the healthcare industry to automate and improve treatments' success rates and empower medical experts to help more people. Medical imaging is also known as computer vision in medicine. Despite some conceptual differences between the terms “computer vision” and “image recognition” or “imaging,” for the purpose of this article, we treat both terms equally.
The global medical imaging market is expected to grow from $37.97B in 2021 to $56.53B in 2028, at a CAGR of 5.8%.
Medical imaging is a promising yet challenging market. Let's delve deeper into it and see why investors look at AI applications in medicine with growing interest.