Aiosyn, a company that develops AI-powered computational pathology analysis for clinical diagnostics, and the department of pathology of Radboud University Medical Center, will collaborate to implement an algorithm for quality control of digitized histopathology tissue slides. They are the first in the Netherlands to do so.
Within a digital pathology workflow, all tissue slides are digitized before examination by a pathologist. Histological slides may show heterogeneity as a result of pre-analytical processing such as fixation, cutting, staining, and scanning. Today, technicians still perform visual quality control of digitized slides which is laborious and has a low throughput.
Aiosyn developed a quality control algorithm that automatically checks for the most common artifacts, such as out of focus areas and tissue folds. In this collaboration, the quality control algorithm, running on Aiosyn’s platform, will be fully integrated into the routine histopathology workflow. This allows the algorithm to flag artifacts and streamline the workflow by ordering slide rescans automatically.
Using automated quality control, Radboudumc ensures the use of continuously high-quality images in histopathology diagnostic. Jeroen van der Laak, professor at Radboudumc and CSO of Aiosyn: ‘It’s great to see that we are now REALLY going to leverage artificial intelligence to improve our patient care.’
Aiosyn is on a mission to accelerate the adoption of artificial intelligence in pathology diagnostics and improve the survival chances of cancer patients worldwide. The company develops AI-powered algorithms that are integrated in the standard histopathology workflow. In addition, Aiosyn’s algorithms are used to accelerate innovation in biopharma and diagnostics companies.
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