Cross-Modality Learning for Predicting Immunohistochemistry Biomarkers from Hematoxylin and Eosin-Stained Whole Slide Images. [PDF]
Das A +8 more
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Deep learning-based histomorphological subtyping and risk stratification of small cell lung cancer from hematoxylin and eosin-stained whole slide images. [PDF]
Zhang Y +13 more
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Scalable, trustworthy generative model for virtual multi-staining from H&E whole slide images. [PDF]
Ounissi M +5 more
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Optimizing Re-staining Techniques for the Restoration of Faded Hematoxylin and Eosin-stained Histopathology Slides: A Comparative Study. [PDF]
Lorsuwannarat N +5 more
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Quantifying the recovery process of skeletal muscle on hematoxylin and eosin stained images via learning from label proportion. [PDF]
Yamaoka Y +5 more
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Cell Segmentation With Globally Optimized Boundaries (CSGO): A Deep Learning Pipeline for Whole-Cell Segmentation in Hematoxylin-and-Eosin-Stained Tissues. [PDF]
Gu Z +15 more
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Distinguishing of Histopathological Staging Features of H-E Stained Human cSCC by Microscopical Multispectral Imaging. [PDF]
Wu R +9 more
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Micro-computed Tomography in the Evaluation of Eosin-stained Axillary Lymph Node Biopsies of Females Diagnosed with Breast Cancer. [PDF]
Laguna-Castro S +6 more
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Annotation-free deep learning algorithm trained on hematoxylin & eosin images predicts epithelial-to-mesenchymal transition phenotype and endocrine response in estrogen receptor-positive breast cancer. [PDF]
Hu K +5 more
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HistoNeXt: dual-mechanism feature pyramid network for cell nuclear segmentation and classification. [PDF]
Chen J, Wang R, Dong W, He H, Wang S.
europepmc +1 more source

