HoloZcan project news
Learning patterns are essential for enabling AI to categorize different micro-objects based on their images.
Generating these patterns poses a particular challenge for holographic microscopes. This is because these systems are highly sensitive to the presence of minuscule objects that are not visible in images produced by conventional microscopes.
In holographic systems, both the refractive index and the light absorption properties of the material are complex variables. To achieve optimal results, our team tests various established preparation methods. These include Gram and nigrosine staining, fixation on polylysine surfaces, and mixing detergents and surfactants with both biological and inert samples.