The Technology
Cancer diagnosis from biopsies traditionally relies on manual microscopic examination by pathologists, a method prone to variability and errors due to increasing demand and shortage of trained personnel. This groundbreaking technology employs advanced spectral imaging combined with artificial intelligence (AI) to automate and significantly enhance the accuracy and speed of cancer diagnosis. The spectral imaging system captures detailed spectral data from biopsy samples, creating unique spectral signatures that differentiate cancerous cells from normal ones. Machine learning algorithms, specifically developed for spectral image segmentation and cancer detection, analyze this data to deliver precise diagnostics rapidly and reliably.
The system has demonstrated excellent performance in accurately identifying multiple cancer types, including challenging subtypes such as certain thyroid cancers, highlighting its substantial diagnostic value. Furthermore, recent advancements have included AI-based virtual staining, eliminating the need for traditional staining methods and streamlining the pathology workflow.
Advantages
- Rapid, accurate, and automated cancer diagnostics
- Significantly reduces diagnostic errors and variability
- Successful segmentation and classification using advanced AI algorithms
- Virtual staining capability, eliminating traditional staining processes
- Adaptable across various cancer types, including complex cases
Applications and Opportunities
- Pathology laboratories in hospitals and research institutions worldwide
- Potential to become the standard diagnostic tool for pathology departments
- Expansion into diagnostics for other complex conditions and hematological malignancies
Business Development Contacts