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

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...

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Bibliographic Details
Main Authors: Angel Cruz-Roa, Gloria Díaz, Eduardo Romero, Fabio A González
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2011-01-01
Series:Journal of Pathology Informatics
Subjects:
Basal Cell Carcinoma
Histopathology Images
Automatic Annotation
Visual Latent Semantic Analysis
Non-negative Matrix Factorization
Bag of Features
Online Access:http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2011;volume=2;issue=2;spage=4;epage=4;aulast=Cruz-Roa

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http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2011;volume=2;issue=2;spage=4;epage=4;aulast=Cruz-Roa

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