The Physics PhD Seminar Series is held over Zoom. One PhD student gives a 15-minute presentation on their work, followed by questions. The presentations are aimed at a general physics audience.
Zoom link: https://gu-se.zoom.us/j/6314424991
Quantitative analysis of cell structures is essential for pharmaceutical drug screening and medical diagnostics. This presentation introduces a deep-learning-powered approach to extract quantitative biological information from brightfield microscopy images. Specifically, we train a conditional generative adversarial neural network (cGAN) to virtually stain lipid droplets, cytoplasm, and nuclei from brightfield images of human adipocytes, which are of particular interest for nanomedicine and vaccine development. Subsequently, we demonstrate that these virtually-stained images can be successfully employed to extract quantitative biologically relevant measures in a downstream cell-profiling analysis.
Link to the paper: https://aip.scitation.org/doi/10.1063/5.0044782
I am a PhD student in the Soft Matter Lab group, supervised by Giovanni Volpe. My research interests include Deep learning, Biophysics, and Biomedical image processing.