Tissue Region

Tissue region analysis focuses on identifying and characterizing distinct areas within tissue samples, aiming to extract meaningful biological information for disease diagnosis and treatment. Current research employs deep learning architectures, such as DenseNet and convolutional neural networks, for automated segmentation and classification of these regions within whole slide images, often incorporating multi-task learning approaches to improve efficiency and accuracy. This work is significantly impacting pathology and related fields by enabling more precise and efficient analysis of tissue samples, leading to improved diagnostic capabilities and a deeper understanding of disease mechanisms.