Evaluating virtual staining for high-throughput screening


Little is known about the feasibility of virtual staining for industry applications such as high-throughput screening (HTS). We provide a thorough analysis of the usability of image-to-image translation for the virtual staining of label-free bright-field microscopy images of live cells, using a pool of more than 1.6 million images across six lung, six ovarian and six breast cell lines consisting of paired bright-field, cytoplasm, nuclei and DNA-damage stains. To our knowledge this is the first time an analysis of virtual staining has been performed on three levels; pixel-based, biological-feature based, and determining if virtual staining can reproduce drug-effect. Our results reveal that while virtually stained nuclei and cytoplasm images often consistently and faithfully reproduce the information found in fluorescence microscopy, virtually stained images of DNA-damage are usually less accurate.

In International Symposium on Biomedical Imaging
Samuel Tonks
Samuel Tonks
PhD Student in Computer Science

My research interests include generative modelling, uncertainty quantification and healthcare applications.