In cooperation with the company KML Vision, scientists at the Medical University of Vienna apply fluorescence techniques and machine learning to raise blood smear microscopy to a new level. They intend to apply AI algorithms to classify White Blood Cells into their respective subtypes and to establish advanced methods of qualitative and quantitative analysis to assess health
states such as acute or chronic inflammation.
The method, which was trained on a dataset of blood smear images, was able to accurately identify and classify the different types of white blood cells, with a higher accuracy for monochromatic images than for color images. The researchers concluded that the IKOSA AI platform provides a valid tool for developing a blood cell detection and classification algorithm, and that the method could have a number of potential applications in research.
View the poster and see how IKOSA supported the research