Virgo’s AI model analyzes endoscopy videos using MetaAI’s DINOv2

MetaAI’s DINOv2 computer vision technology is enabling Virgo, a San Diego-based medical company, to analyze endoscopy videos using artificial intelligence, with the goal of improving patient outcomes and advancing precision medicine.

The innovation: Virgo has developed VirgoCloud, a system that captures and processes endoscopy videos, while also creating AutoIBD, an AI model that identifies potential candidates for inflammatory bowel disease clinical trials.

• The company has amassed over 1.75 million procedure videos, reportedly the largest dataset of its kind
• VirgoCloud connects to existing endoscopic equipment to capture, compress, and encrypt procedure videos
• The system transmits data to a HIPAA-compliant web portal for secure storage and analysis

Technical integration: Virgo incorporated Meta’s open-source DINOv2 technology into their system, leading to significant performance improvements in their AI models.

• DINOv2 serves as a feature extractor for computer vision, enabling efficient analysis of vast amounts of video data
• The company used DINOv2’s architecture to develop EndoDINO, their specialized AI foundation model for endoscopy
• EndoDINO has achieved leading performance in various endoscopy-related AI benchmarks, including anatomical landmark classification and disease severity scoring

Clinical applications: The technology shows promise in advancing precision medicine and improving patient care through various applications.

• The system can predict patient characteristics like age, sex, and BMI from colonoscopy data
• EndoDINO may help determine the likelihood of clinical remission from IBD with specific drug treatments
• Hospitals could potentially develop customized models for real-time polyp detection and classification

Industry collaboration: Virgo is making their technology available through a development platform called EndoML.

• Pharmaceutical companies and academic medical centers can access EndoDINO for research and development
• Dr. Ali Soroush from Mount Sinai’s Icahn School of Medicine highlights the model’s potential for uncovering new patterns in endoscopy
• The platform enables rapid development of AI applications tailored to specific medical needs

Future implications: Self-supervised learning and AI analysis of endoscopy videos could reshape gastroenterological care and precision medicine, though questions remain about widespread adoption and integration into existing medical workflows.

• The technology could improve clinical trial recruitment and patient treatment matching
• Healthcare providers might develop institution-specific AI models for their patient populations
• Success will depend on continued validation of the technology’s accuracy and clinical utility