Machine Learning-Supported Analyses Improve Quantitative Histological Assessments of Amyloid-β Deposits and Activated Microglia

BACKGROUND: Detailed pathology analysis and morphological quantification is tedious and prone to errors. Automatic image analysis can help to increase objectivity and reduce time. Here, we present the evaluation of the DeePathology STUDIO™ for automatic analysis of histological whole-slide images us...

Descripción completa

Detalles Bibliográficos
Autores principales: Bascuñana, Pablo, Brackhan, Mirjam, Pahnke, Jens
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOS Press 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7902967/
https://www.ncbi.nlm.nih.gov/pubmed/33337377
http://dx.doi.org/10.3233/JAD-201120

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7902967/
https://www.ncbi.nlm.nih.gov/pubmed/33337377
http://dx.doi.org/10.3233/JAD-201120

Ejemplares similares