Automated HER2 Scoring in Breast Cancer Images Using Deep Learning and Pyramid Sampling

arXiv:2404.00837v1 Announce Type: cross
Abstract: Human epidermal growth factor receptor 2 (HER2) is a critical protein in cancer cell growth that signifies the aggressiveness of breast cancer (BC) and helps predict its prognosis. Accurate assessment of immunohistochemically (IHC) stained tissue slides for HER2 expression levels is essential for both treatment guidance and understanding of cancer mechanisms. Nevertheless, the traditional workflow of manual examination by board-certified pathologists encounters challenges, including inter- and intra-observer inconsistency and extended turnaround times. Here, we introduce …

abstract arxiv assessment automated cancer cs.cv cs.lg deep learning eess.iv growth human images physics.med-ph protein pyramid sampling scoring slides type