Whole Slide Image

Whole slide images (WSIs) are gigapixel-scale digital representations of tissue samples, crucial for pathology. Research focuses on developing efficient and accurate algorithms, often employing deep learning architectures like transformers and graph neural networks within multiple instance learning (MIL) frameworks, to classify WSIs, predict patient outcomes (e.g., survival, treatment response), and detect biomarkers from the images. These advancements aim to improve diagnostic accuracy, personalize treatment strategies, and accelerate the analysis of large WSI datasets, ultimately impacting both research and clinical practice in pathology.