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2025
Autores
Klöckner, P; Teixeira, J; Montezuma, D; Fraga, J; Horlings, HM; Cardoso, JS; Oliveira, SP;
Publicação
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.
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