Self-supervised Learning for Tumor Microenvironment Analysis: Addressing Label Scarcity in Multiplexed Immunofluorescence Imaging with Novel Feature Extraction Techniques

The study of tumor microenvironments (TMEs) and immune cell composition in cancer, a disease characterized by uncontrolled growth and spread of tumor cells, has become increasingly important for understanding tumor progression and patient outcomes. Tools such as the TME-Analyzer enable this kind of research, but their manual workflows highlight...

Detecting structural heterogeneity in single-molecule localization microscopy data

<br/>For decades, the resolution of fluorescent light microscopy has been bounded by Abbe’s diffraction limit to λ/2NA. Super-resolution methods, awarded with the 2014 Nobel Prize in Chemistry, use tricks to overcome this limit. The general idea is to image blinking fluorophores for a multitude of frames, such that each frame only contains a...