Mitosis Detection

Mitosis detection, the automated identification of dividing cells in microscopy images, aims to improve the speed and accuracy of cancer diagnosis and other biological research. Current research heavily utilizes deep learning, employing architectures like convolutional neural networks (CNNs), U-Nets, and RetinaNets, often within two-stage frameworks combining detection and classification. These models are being enhanced through techniques such as data augmentation, hard negative mining, and the integration of vision-language models to address challenges like inter-observer variability and domain shifts across different imaging conditions. Improved automated mitosis detection promises to significantly reduce the time and effort required for manual analysis, leading to more efficient and consistent diagnoses and a deeper understanding of cellular processes.