Gleamer, a French AI-driven radiology software provider, is expanding its capabilities beyond X-ray and mammography analysis to include magnetic resonance imaging (MRI).
Highlights
To support this growth, the company has acquired Pixyl and Caerus Medical, two startups specializing in AI-powered MRI analysis.
Strategic Expansion into MRI
Rather than developing an MRI solution from the ground up, Gleamer plans to integrate the technologies of Pixyl and Caerus Medical to broaden its AI applications in MRI diagnostics.
This approach aligns with the company’s objective of enhancing diagnostic accuracy through AI-driven imaging solutions.
| Metric | Gleamer AI Imaging | Traditional Radiology |
|---|---|---|
| Diagnostic Accuracy | High accuracy with AI-enhanced analysis, leveraging extensive datasets | Variable accuracy; relies on manual interpretation and standard imaging |
| Processing Speed | Rapid processing—up to 2,000 pages/min per node | Slower, manual review processes lead to longer turnaround times |
| Regulatory Approvals | CE and FDA approved for multiple AI-driven radiology tools | Standard certifications without advanced AI validation |
| Data Integration | Structured outputs (Markdown, JSON) for seamless AI workflow integration | Often unstructured, requiring additional manual processing |
Founded in 2017, Gleamer has established itself as an AI assistant for radiologists, helping improve medical imaging interpretation. Its AI models are currently deployed in 2,000 institutions across 45 countries, processing 35 million examinations to date.
The company holds CE and FDA approvals for its bone trauma detection tool and offers AI-powered analysis for chest X-rays, orthopedic imaging, and bone age assessments.
Recently, it introduced an AI model for mammography, trained on 1.5 million scans, which demonstrated improved cancer detection rates.
Challenges and Approach to MRI Analysis
MRI diagnostics differ significantly from X-rays and CT scans, as they involve complex tasks such as segmentation, detection, characterization, and classification.
CEO Christian Allouche has highlighted that a “one-size-fits-all approach” is not effective in radiology, necessitating a targeted AI strategy. The acquisitions of Pixyl and Caerus Medical allow Gleamer to leverage existing expertise and accelerate the development of MRI-focused AI tools.
Funding and Expansion Plans
In June 2023, Gleamer secured €27 million in Series B funding, led by Supernova Invest, with participation from Heal Capital, XAnge, Elaia, Bpifrance, MACSF, Crista Galli Ventures, and UI Investissement. This investment aims to support:
- Expansion of AI solutions for medical imaging
- Acceleration of international growth
Additionally, Gleamer is advancing its OncoView project, an AI initiative focused on detecting, measuring, and monitoring cancerous lesions, particularly in lung and bone tissues.
This project has received €4.5 million in co-funding from the French government’s France 2030 program, contributing to a total investment of €18 million over five years.
Integration of Acquired Technologies
The integration of Pixyl and Caerus Medical’s technologies will complement Gleamer’s existing AI-powered imaging solutions, which include:
- BoneView – AI for bone trauma lesion detection
- ChestView – AI for pulmonary pathology analysis
- BoneMeasurement – AI for musculoskeletal assessments
- BoneAge – AI for bone age estimation
These solutions hold MDR Class IIa CE certification in Europe, underscoring their regulatory compliance and clinical reliability.
Future of AI in Medical Imaging
AI-driven medical imaging is increasingly being viewed as an essential tool for addressing the growing demand for radiology services. With many healthcare systems facing radiologist shortages, AI solutions can enhance efficiency and diagnostic accuracy.
Looking ahead, AI could play a role in preventive medical imaging, enabling routine full-body MRI scans for early disease detection.
While financial details of the Pixyl and Caerus Medical acquisitions have not been disclosed, Gleamer’s focus remains on leveraging AI to make medical imaging faster, more precise, and more widely accessible.
