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Authors: Imene Cheikhrouhou 1 ; Khalifa Djemal 1 ; Dorra Sellami Masmoudi 2 ; Hichem Maaref 1 and Nabil Derbel 2

Affiliations: 1 University of Evry Val dEssonne (UEVE), France ; 2 National Engineering school of Sfax (ENIS), Tunisia

Abstract: In breast cancer field, radiologists and researchers aim to discriminate between masses due to benign breast diseases and tumors due to breast cancer. In general, benign masses have circumscribed contours, whereas, malignant tumors appear with spiculated and irregular boundaries. Recently, we proposed an original mass description based on three morphological mass descriptors, which are SPICULation (SPICUL), Contour Derivative Variation (CDV) and Skeleton End Points (SEP). In this paper, we detail an empirical mass evaluation based on these morphological descriptors which intend to distinguish between malignant and benign lesions. This evaluation is, first, assured by following descriptors evolution in two independent data sets: Alberta and MIAS. Secondly, for these two data sets, the Receiver Operating Characteristics (ROC) analysis is applied. A comparison between the classic use of Area (A) and Perimeter (P) descriptors only, and a combination with our three original evaluated desc riptors is done. Obtained results proves that classification accuracy of the descriptors combination including: SPICUL, SEP, CDV, A and P outperforms that of the classic descriptors: A and P. Indeed, our original mass description provides the best Area under ROC Az = 0.986 for Alberta data set and Az = 0.9792 for the MIAS data set. Therefore, we affirm that our three original descriptors can serve as good shape descriptors for the benign-versus-malignant classification of breast masses on mammograms. (More)

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Paper citation in several formats:
Cheikhrouhou, I.; Djemal, K.; Sellami Masmoudi, D.; Maaref, H. and Derbel, N. (2009). Empirical Descriptors Evaluation for Mass Malignity Recognition. In Proceedings of the 1st International Workshop on Medical Image Analysis and Description for Diagnosis Systems (BIOSTEC 2009) - Workshop MIAD; ISBN 978-989-8111-77-7, SciTePress, pages 91-100. DOI: 10.5220/0001815400910100

@conference{workshop miad09,
author={Imene Cheikhrouhou. and Khalifa Djemal. and Dorra {Sellami Masmoudi}. and Hichem Maaref. and Nabil Derbel.},
title={Empirical Descriptors Evaluation for Mass Malignity Recognition},
booktitle={Proceedings of the 1st International Workshop on Medical Image Analysis and Description for Diagnosis Systems (BIOSTEC 2009) - Workshop MIAD},
year={2009},
pages={91-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001815400910100},
isbn={978-989-8111-77-7},
}

TY - CONF

JO - Proceedings of the 1st International Workshop on Medical Image Analysis and Description for Diagnosis Systems (BIOSTEC 2009) - Workshop MIAD
TI - Empirical Descriptors Evaluation for Mass Malignity Recognition
SN - 978-989-8111-77-7
AU - Cheikhrouhou, I.
AU - Djemal, K.
AU - Sellami Masmoudi, D.
AU - Maaref, H.
AU - Derbel, N.
PY - 2009
SP - 91
EP - 100
DO - 10.5220/0001815400910100
PB - SciTePress