We provide an AI-powered solution to aid research labs with the identification of mitotic figures in H&E sections1.
The manual process is time-consuming and subject to variability, and there is a need for solutions to increase its efficiency and consistency of results. Aiosyn Mitosis – Breast uses deep learning to detect mitosis in whole slide images, saving pathologists time and providing research labs with a more standard process. With enhanced and reproducible detection, new biomarkers can be discovered and researched more accurately.
1. Aiosyn is in process of validating the use of Aiosyn Mitosis – Breast for clinical diagnostics and it is undergoing CE-mark certification under the EU IVDR. Currently, the use of Aiosyn Mitosis – Breast is limited to performance studies / Research Use Only. Not for use in diagnostic procedures.
Aiosyn Mitosis – Breast helps research labs improve the process of mitosis analysis. The algorithm detects and highlights mitotic figures in H&E slides, saving pathologists time.
AI-powered mitosis detection improves the consistency of research data by reducing observer variability and providing unified criteria for the analysis of mitotic figures.
Aiosyn Mitosis – Breast is offered as a modular software solution that can be integrated into existing workflows, removing the need to adopt a different viewer.
Our Aiosyn Mitosis – Breast can be integrated with major workflow providers such as Sectra. Slides are prepared as usual, and the algorithm analyzes images once uploaded to the platform.
Aiosyn Mitosis – Breast automatically recognizes and highlights mitotic bodies in H&E slides to improve the quality and speed of the tumor grading process. Tightly integrated into existing workflows, this application advances pathology research, prevents delays, and improves the consistency of results.