Cargando…
Pan-tumor CAnine cuTaneous Cancer Histology (CATCH) dataset
Due to morphological similarities, the differentiation of histologic sections of cutaneous tumors into individual subtypes can be challenging. Recently, deep learning-based approaches have proven their potential for supporting pathologists in this regard. However, many of these supervised algorithms...
Autores principales: | Wilm, Frauke, Fragoso, Marco, Marzahl, Christian, Qiu, Jingna, Puget, Chloé, Diehl, Laura, Bertram, Christof A., Klopfleisch, Robert, Maier, Andreas, Breininger, Katharina, Aubreville, Marc |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9515104/ https://www.ncbi.nlm.nih.gov/pubmed/36167846 http://dx.doi.org/10.1038/s41597-022-01692-w |
Ejemplares similares
-
A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor
por: Bertram, Christof A., et al.
Publicado: (2019) -
Inter-species cell detection - datasets on pulmonary hemosiderophages in equine, human and feline specimens
por: Marzahl, Christian, et al.
Publicado: (2022) -
Automated diagnosis of 7 canine skin tumors using machine learning on H&E-stained whole slide images
por: Fragoso-Garcia, Marco, et al.
Publicado: (2023) -
A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research
por: Aubreville, Marc, et al.
Publicado: (2020) -
Pan-tumor T-lymphocyte detection using deep neural networks: Recommendations for transfer learning in immunohistochemistry
por: Wilm, Frauke, et al.
Publicado: (2023)