Digital staining with confidence estimation for hematological imaging
This project investigated the reliability of generative image translation for digital staining of hematological microscopy images, aiming to reduce variability and processing time in laboratory workflows while preserving diagnostically relevant structures.
Abstract
Collaborators: PD Dr.\ Slobodan Ilic (Siemens AG)
This project investigated the reliability of generative image translation for digital staining of hematological microscopy images, aiming to reduce variability and processing time in laboratory workflows while preserving diagnostically relevant structures. Using paired unstained and chemically stained microscopy images from 24 patients, we developed a style–structure disentangled generative framework with an associated confidence estimation that quantifies output reliability via latent perturbations. The confidence score correlated strongly with perceptual image quality and enabled the identification of unreliable synthetic samples.
Our role
Contributing collaborator with responsibility for methodological development and uncertainty estimation; doctoral supervision and mentorship conducted in close collaboration with academic and industrial partners.
Perspective
The project contributed to the successful doctoral training of an external PhD candidate and established methodological foundations for later work on uncertainty estimation and trust in medical image generation. It exemplifies sustained national collaboration between academia and industry.
