Histology Slide

Histology slides, digitized as whole slide images (WSIs), are analyzed using computational pathology to improve diagnostic accuracy and efficiency in various medical fields. Current research focuses on developing robust deep learning models, including vision transformers and multiple instance learning (MIL) frameworks, often enhanced with techniques like stain normalization and prompt learning, to address challenges such as limited annotated data and stain variation. These advancements aim to automate tasks like cancer subtyping, grading, and prognostic prediction, ultimately improving patient care and accelerating research discoveries.