Multiplexed Immunofluorescence

Multiplexed immunofluorescence (mIF) is a powerful imaging technique enabling simultaneous visualization of multiple biomarkers within tissue samples, providing rich insights into cellular interactions and tissue microenvironments. Current research focuses on developing automated image analysis pipelines using machine learning, particularly graph neural networks and generative adversarial networks (GANs), to overcome challenges like cell segmentation, alignment of different imaging modalities (e.g., H&E and mIF), and efficient feature extraction from high-dimensional data. These advancements are significantly improving the speed and accuracy of mIF data analysis, facilitating deeper biological understanding in diverse fields like cancer research and immunology, and ultimately aiding in improved diagnostics and personalized medicine.

Papers