Diagnostic imaging specialist RadNet has agreed to acquire French clinical artificial intelligence (AI)-focused company, Gleamer, for up to €230m ($267.2m).
Through this acquisition, RadNet will gain access to Gleamer’s four US Food and Drug Administration (FDA) approved and six CE-marked radiology AI tools and services, which are designed to automate the routine imaging process to improve efficiency and enhance diagnostic accuracy. Gleamer’s portfolio includes several clinical AI tools spanning multiple modalities and disease indications – including lung, breast and neurological applications.
Under the terms of the agreement, RadNet’s wholly owned health informatics division, DeepHealth, will absorb Gleamer’s team of 130 employees, as well as its customer base spanning 44 countries. The cloud-first company currently serves more than 700 contracts across the globe, which include healthcare systems, hospitals and imaging centres.
By combining its portfolio with Gleamer’s, RadNet will offer services spanning screening, detection, interpretation and follow-up across neurodegenerative and musculoskeletal conditions, as well as a large proportion of the prevalent cancer types.
RadNet will pay Gleamer up to €230m in cash – including a post-closing milestone – through the buyout.
According to RadNet, Gleamer’s portfolio is likely to “create measurable productivity gains” for the company. RadNet says that this is especially true in X-ray, which currently accounts for 25% of its imaging volume. The company adds that the introduction of Gleamer’s draft reporting capabilities will also allow radiologists to enhance the accuracy and volume of imaging reading – driving efficiencies in operations and cost.
As is the case across the wider technology industry, AI is having a significant impact on the healthcare sector.
This comes as digital giants OpenAI and Anthropic both unveil AI-driven healthcare toolkits, which are designed to support providers, payers and patients. According to a report from GlobalData, this could put traditional software companies under growing pressure, as these tools may “replicate and potentially surpass” their core value.
Within the imaging and diagnostics landscape, there has also been a notable drive to incorporate AI. An example of a company taking this approach is GE Healthcare, which recently launched the next generation of its LOGIQ ultrasound systems. GE built clinical imaging tools in this portfolio to streamline the diagnostics process, allow for early disease detection, and enable effective progression monitoring.
