Aiosyn, a software company that develops AI-powered pathology software, has launched its first product that assists digital pathology labs across research, diagnostics and pharma to improve their quality control (QC) process.
AiosynQC is an AI-powered algorithm that automatically scans for the most common artifacts that occur during the heterogeneous pre-analytical process. The algorithm of AiosynQC is trained on hematoxylin and eosin (H&E) stained slides. The product helps labs to ensure that only high-quality images are used by pathologists, technicians, and researchers. It can flag cases before presentation to a pathologist, thereby improving the efficiency of the digital pathology workflow by reducing the time that is currently used to manually check for artifacts in whole slide images.
Illustrated above is a demonstration of how out-of-focus regions of an H&E stained slide image, are identified and highlighted with Aiosyn's automated quality control powered by AI.
AiosynQC is a modular and flexible software offered as a service solution that can be integrated into existing digital pathology software and deployed through the cloud or on-premises installation. The automated QC is the first product in Aiosyn’s workflow solutions suite. It will be part of a portfolio of deep learning algorithms currently in development for different pathologies for which there is a clear need to improve diagnostic precision and quality.
“AiosynQC will be an important foundational layer and we believe that AI-powered workflow solutions are the entry point for the use and adoption of computational pathology algorithms” according to Patrick de Boer, CEO of Aiosyn.
For more information visit - www.aiosyn.com/automated-quality-control/.
