Tissue Image

Tissue image analysis is a rapidly evolving field focused on extracting meaningful information from microscopic images of biological tissues, primarily for diagnostic and prognostic purposes in medicine. Current research heavily utilizes deep learning, employing architectures like U-Nets, Vision Transformers, and generative adversarial networks (GANs) for tasks such as cell segmentation, classification, and whole-slide image analysis, often incorporating multiple instance learning (MIL) to handle the inherent heterogeneity of tissue samples. These advancements are improving diagnostic accuracy, enabling the discovery of novel biomarkers, and accelerating the development of personalized medicine approaches by automating laborious manual processes and providing quantitative insights into tissue morphology and composition.