Cell Counting

Cell counting, a fundamental task in many biological and medical fields, aims to accurately quantify the number and types of cells in images, often microscopy images. Current research focuses on developing automated cell counting methods using deep learning models like DETR and YOLO, addressing challenges such as variations in imaging conditions, cell morphology, and class imbalances through techniques such as disentangled transfer learning and efficient annotation pipelines. These advancements significantly improve efficiency and accuracy compared to manual counting, impacting diverse areas including neuroscience, developmental biology, and clinical diagnostics by enabling high-throughput analysis and reducing human bias.