Microscopy Video

Microscopy video analysis focuses on automatically extracting meaningful information from time-lapse microscopy images, primarily for cell tracking and object detection in diverse biological contexts. Current research emphasizes the application of deep learning, particularly graph neural networks and novel architectures like Double Branch Feature Extraction Networks, to improve accuracy and efficiency in tasks such as identifying individual cells, tracking their movement and division, and detecting impurities. These advancements are crucial for accelerating biological research, enabling high-throughput analysis, and improving the accessibility of advanced microscopy techniques, particularly in resource-limited settings through innovative digitization workflows.