Fluorescent Based

Fluorescent-based techniques are revolutionizing various scientific fields by providing high-resolution imaging and quantitative data for diverse applications, from medical diagnostics to materials science. Current research focuses on improving the efficiency and accuracy of fluorescence microscopy through advanced computational methods, including deep learning architectures like convolutional neural networks and autoencoders, and novel algorithms for image processing, such as deconvolution and signal unmixing. These advancements are enabling more precise and efficient analysis of complex biological systems, improving diagnostic capabilities in medicine, and facilitating breakthroughs in materials characterization and other scientific domains.