Tissue Context

Tissue context analysis focuses on understanding the spatial relationships and interactions within biological tissues to improve diagnostics and treatment. Current research heavily utilizes deep learning, employing architectures like convolutional neural networks, vision transformers, and graph transformers, often within a multiple instance learning framework to process high-resolution images (e.g., whole slide images) and extract meaningful features from diverse tissue types. This work is significant for advancing automated pathology, enabling more precise and efficient disease diagnosis, and facilitating personalized medicine through improved image analysis and biomechanical modeling.