Prognostic Classification of Early Ovarian Cancer Based on very Low Dimensionality Adaptive Texture Feature Vectors from Cell Nuclei from Monolayers and Histological Sections

In order to study the prognostic value of quantifying the chromatin structure of cell nuclei from patients with early ovarian cancer, low dimensionality adaptive fractal and Gray Level Cooccurrence Matrix texture feature vectors were extracted from nuclei images of monolayers and histological sectio...

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Detalles Bibliográficos
Autores principales: Nielsen, Birgitte, Albregtsen, Fritz, Kildal, Wanja, Danielsen, Håvard E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOS Press 2001
Materias:
Other
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4618001/
https://www.ncbi.nlm.nih.gov/pubmed/11904463
http://dx.doi.org/10.1155/2001/683747

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4618001/
https://www.ncbi.nlm.nih.gov/pubmed/11904463
http://dx.doi.org/10.1155/2001/683747

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