Cell Detection

Cell detection, the automated identification of individual cells within images, is crucial for accelerating biomedical research and improving diagnostics. Current research emphasizes improving accuracy and efficiency, particularly in challenging scenarios like densely packed cells, overlapping cells and tissues, and imbalanced datasets, often employing deep learning models such as convolutional neural networks (CNNs), vision transformers (ViTs), and graph neural networks (GNNs), sometimes enhanced with attention mechanisms or incorporating prior biological knowledge. These advancements are significantly impacting fields like pathology, where automated cell detection aids in faster and more objective diagnoses of diseases such as cancer, and in other areas of biology where high-throughput cell analysis is needed.