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Authors: Filip Florea 1 ; Eugen Barbu 2 ; Alexandrina Rogozan 1 and Abdelaziz Bensrhair 1

Affiliations: 1 LITIS Laboratory, INSA de Rouen, France ; 2 LITIS Laboratory, University of Rouen, France

Abstract: Our work is focused on the automatic categorization of medical images according to their visual content for indexing and retrieval purposes in the context of the CISMeF health-catalogue. The aim of this study is to assess the performance of our medical image categorization algorithm according to the image’s modality, anatomic region and view angle. For this purpose we represented the medical images using texture and statistical features. The high dimensionality led us to transform this representation into a symbolic description, using block labels obtained after a clustering procedure. A medical image database of 10322 images, representing 33 classes was selected by an experienced radiologist. The classes are defined considering the images medical modality, anatomical region and acquisition view angle. An average precision of approximately 83% was obtained using k-NN classifiers, and a top performance of 91.19% was attained with 1-NN when categorizing the images with respect to the d efined 33 classes. The performances raise to 93.62% classification accuracy when only the modality is needed. The experiments we present in this paper show that the considered image representation obtains high recognition rates, despite the difficult context of medical imaging. (More)

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Paper citation in several formats:
Florea, F.; Barbu, E.; Rogozan, A. and Bensrhair, A. (2006). Multi-modal Categorization of Medical Images Using Texture-based Symbolic Representations. In 6th International Workshop on Pattern Recognition in Information Systems (ICEIS 2006) - PRIS; ISBN 978-972-8865-55-9, SciTePress, pages 48-57. DOI: 10.5220/0002500300480057

@conference{pris06,
author={Filip Florea. and Eugen Barbu. and Alexandrina Rogozan. and Abdelaziz Bensrhair.},
title={Multi-modal Categorization of Medical Images Using Texture-based Symbolic Representations},
booktitle={6th International Workshop on Pattern Recognition in Information Systems (ICEIS 2006) - PRIS},
year={2006},
pages={48-57},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002500300480057},
isbn={978-972-8865-55-9},
}

TY - CONF

JO - 6th International Workshop on Pattern Recognition in Information Systems (ICEIS 2006) - PRIS
TI - Multi-modal Categorization of Medical Images Using Texture-based Symbolic Representations
SN - 978-972-8865-55-9
AU - Florea, F.
AU - Barbu, E.
AU - Rogozan, A.
AU - Bensrhair, A.
PY - 2006
SP - 48
EP - 57
DO - 10.5220/0002500300480057
PB - SciTePress

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