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Proceedings Paper

A statistical model for characterization of histopathology images
Author(s): Pablo Álvarez; Guatizalema Castro; Germán Corredor; Eduardo Romero
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Paper Abstract

Accessing information of interest in collections of histopathology images is a challenging task. To address such issue, previous works have designed searching strategies based on the use of keywords and low-level features. However, those methods have demonstrated to not be enough or practical for this purpose. Alternative low-level features such as cell area, distance among cells and cell density are directly associated to simple histological concepts and could serve as good descriptors for this purpose. In this paper, a statistical model is adapted to represent the distribution of the areas occupied by cells for its use in whole histopathology image characterization. This novel descriptor facilitates the design of metrics based on distribution parameters and also provides new elements for a better image understanding. The proposed model was validated using image processing and statistical techniques. Results showed low error rates, demonstrating the accuracy of the model.

Paper Details

Date Published: 28 January 2015
PDF: 6 pages
Proc. SPIE 9287, 10th International Symposium on Medical Information Processing and Analysis, 92870H (28 January 2015); doi: 10.1117/12.2073530
Show Author Affiliations
Pablo Álvarez, Univ. Nacional de Colombia (Colombia)
Guatizalema Castro, Univ. Nacional de Educación a Distancia (Spain)
Germán Corredor, Univ. Nacional de Colombia (Colombia)
Eduardo Romero, Univ. Nacional de Colombia (Colombia)


Published in SPIE Proceedings Vol. 9287:
10th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore, Editor(s)

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