Automatic annotation of histopathological images using a latent topic model based on non-negative matrix factorization

Histopathological images are an important resource for clinical diagnosis and biomedical research. From an image understanding point of view, the automatic annotation of these images is a challenging problem. This paper presents a new method for automatic histopathological image annotation based on...

Full description

Autores:
Cruz Roa, Angel Alfonso
Díaz Cabrera, Gloria Mercedes
Romero Castro, Eduardo
González Osorio, Fabio Augusto
Tipo de recurso:
Article of journal
Fecha de publicación:
2012
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/9021
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/9021
http://bdigital.unal.edu.co/5770/
Palabra clave:
6 Tecnología (ciencias aplicadas) / Technology
61 Ciencias médicas; Medicina / Medicine and health
Basal Cell Carcinoma
Histopathology Images
Automatic Annotation
Visual Latent Semantic Analysis
Non-negative Matrix Factorization
Bag of Features
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional