. Segmenting Invasive and In Situ Carcinoma in Breast WSIs with a Pretrained Histopathology Transformer. In 2nd Deep Breast Workshop on AI and Imaging for Diagnostic and Treatment Challenges in Breast Care - MICCAI2025. Daejeon, South Korea: Springer LNCS vol 16142; 2025.
Abstract
Accurately distinguishing between invasive carcinoma (IC) and carcinoma in situ (CIS) in breast histopathology is essential for diagnosis and staging, and can inform treatment planning. As digital pathology workflows increasingly integrate AI-based tools, automating this distinction in whole slide images (WSIs) remains a critical challenge due to the subtle morphological differences and the limited availability of detailed annotations.
