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AIRS
2008
Springer

A Semantic Content-Based Retrieval Method for Histopathology Images

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A Semantic Content-Based Retrieval Method for Histopathology Images
This paper proposes a model for content-based retrieval of histopathology images. The most remarkable characteristic of the proposed model is that it is able to extract high-level features that reflect the semantic content of the images. This is accomplished by a semantic mapper that maps conventional low-level features to high-level features using state-of-the-art machine-learning techniques. The semantic mapper is trained using images labeled by a pathologist. The system was tested on a collection of 1502 histopathology images and the performance assessed using standard measures. The results show an improvement from a 67% of average precision for the first result, using low-level features, to 80% of precision using high-level features.
Juan C. Caicedo, Fabio A. González, Eduardo
Added 01 Jun 2010
Updated 01 Jun 2010
Type Conference
Year 2008
Where AIRS
Authors Juan C. Caicedo, Fabio A. González, Eduardo Romero
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