H&E to IHC virtual staining methods in breast cancer: an overview and benchmarking - Pascal Klöckner; José Teixeira; Diana Montezuma; João Fraga; Hugo M. Horlings; Jaime S. Cardoso; Sara P. Oliveira (npj Digital Medicine)
Abstract Immunohistochemistry (IHC) is crucial for the clinical categorisation of breast cancer cases. Deep generative models may offer a cost-effective alternative by virtually generating IHC images from hematoxylin and eosin samples. This review explores the state-of-the-art in virtual staining for breast cancer biomarkers (HER2, PgR, ER and Ki-67) and benchmarks several models on public datasets. It serves as a resource for researchers and clinicians interested in applying or developing virtual staining techniques.