A hybrid approach for Pap-Smear cell nucleus extraction

Authors:
M. Orozco-Monteagudo;Hichem Sahli;Cosmin Mihai;A. Taboada-Crispi
Affiliations:
Universidad Central de Las Villas, Cuba;Vrije Universiteit Brussel, Electronics and Informatics Dept. - ETRO, Brussels, Belgium;Vrije Universiteit Brussel, Electronics and Informatics Dept. - ETRO, Brussels, Belgium;Universidad Central de Las Villas, Cuba
Venue:
MCPR'11 Proceedings of the Third Mexican conference on Pattern recognition
Year:
2011

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Abstract

This paper, proposes a two-phases approach for a computerassisted screening system that aims at early diagnosis of cervical cancer in Pap smear images and accurate segmentation of nuclei. The first phase uses spectral, shape as well as the class membership to produce a nested hierarchical partition (hierarchy of segmentations). The second phase, selects the best hierarchical level based on an unsupervised criterion, and refines the obtained segmentation by classifying the individual regions using a Support Vector Machine (SVM) classifier followed by merging adjacent regions belonging to the same class. The effectiveness of the proposed approach for producing a better separation of nucleus regions and cytoplasm areas is demonstrated using both ground truth data, being manually segmented images by pathologist experts, and comparison with state-of-art methods.