Whole Slide Image Classification

Whole slide image (WSI) classification uses machine learning to automatically diagnose diseases from gigapixel-sized pathology scans, aiming to improve efficiency and accuracy in medical diagnosis. Current research heavily utilizes multiple instance learning (MIL) frameworks, often incorporating transformer architectures and attention mechanisms to effectively aggregate information from individual image patches and address class imbalances. These advancements are significantly impacting the field of digital pathology by potentially accelerating diagnosis, improving diagnostic consistency, and enabling more efficient analysis of large datasets.