Fluorescence Image

Fluorescence image analysis is crucial for various biological and medical applications, aiming to extract quantitative and qualitative information from microscopic images. Current research heavily utilizes deep learning, employing architectures like encoder-decoder networks, generative adversarial networks (GANs), and vision transformers to improve image quality (denoising, contrast enhancement), automate cell detection and tracking, and enable accurate segmentation even with limited labeled data. These advancements are significantly impacting fields like biomedical research and clinical diagnostics, facilitating more precise and efficient analysis of cellular processes and disease states.