Cell Morphology

Cell morphology research focuses on understanding and quantifying the shapes and structures of cells, crucial for deciphering biological processes and disease mechanisms. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs), transformers, and other architectures like masked autoencoders, to analyze microscopy images, segment cells, and extract morphological features for classification and prediction tasks. These advancements enable high-throughput analysis of cell populations, improving accuracy in tasks such as cancer subtype identification and drug discovery, while also addressing challenges like optical aberrations and data scarcity. The resulting insights are transforming biomedical research and diagnostics by providing more precise and efficient tools for analyzing cellular behavior and disease states.