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Authors: Ihtesham Ul Islam ; Santa Di Cataldo ; Andrea Bottino ; Elisa Ficarra and Enrico Macii

Affiliation: Politecnico di Torino, Italy

ISBN: 978-989-8565-35-8

Keyword(s): HEp-2 cells, Indirect ImmunoFluorescence, Staining Pattern Classification, Support Vector Machines, Subclass Discriminant Analysis, Image Processing.

Related Ontology Subjects/Areas/Topics: Bioinformatics ; Biomedical Engineering ; Data Mining and Machine Learning ; Image Analysis ; Immuno- and Chemo-Informatics ; Pattern Recognition, Clustering and Classification

Abstract: Anti-nuclear antibodies test is based on the visual evaluation of the intensity and staining pattern in HEp-2 cell slides by means of indirect immunofluorescence (IIF) imaging, revealing the presence of autoantibodies responsible for important immune pathologies. In particular, the categorization of the staining pattern is crucial for differential diagnosis, because it provides information about autoantibodies type. Their manual classification is very time-consuming and not very reliable, since it depends on the subjectivity and on the experience of the specialist. This motivates the growing demand for computer-aided solutions able to perform staining pattern classification in a fully automated way. In this work we compare two classification techniques, based respectively on Support Vector Machines and Subclass Discriminant Analysis. A set of textural features characterizing the available samples are first extracted. Then, a feature selection scheme is applied in order to produce diff erent datasets, containing a limited number of image attributes that are best suited to the classification purpose. Experiments on IIF images showed that our computer-aided method is able to identify staining patterns with an average accuracy of about 91% and demonstrate, in this specific problem, a better performance of Subclass Discriminant Analysis with respect to Support Vector Machines. (More)

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Paper citation in several formats:
Ul Islam, I.; Di Cataldo, S.; Bottino, A.; Ficarra, E. and Macii, E. (2013). Classification of HEp-2 Staining Patterns in ImmunoFluorescence Images - Comparison of Support Vector Machines and Subclass Discriminant Analysis Strategies.In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2013) ISBN 978-989-8565-35-8, pages 53-61. DOI: 10.5220/0004244100530061

@conference{bioinformatics13,
author={Ihtesham Ul Islam. and Santa Di Cataldo. and Andrea Bottino. and Elisa Ficarra. and Enrico Macii.},
title={Classification of HEp-2 Staining Patterns in ImmunoFluorescence Images - Comparison of Support Vector Machines and Subclass Discriminant Analysis Strategies},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2013)},
year={2013},
pages={53-61},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004244100530061},
isbn={978-989-8565-35-8},
}

TY - CONF

JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2013)
TI - Classification of HEp-2 Staining Patterns in ImmunoFluorescence Images - Comparison of Support Vector Machines and Subclass Discriminant Analysis Strategies
SN - 978-989-8565-35-8
AU - Ul Islam, I.
AU - Di Cataldo, S.
AU - Bottino, A.
AU - Ficarra, E.
AU - Macii, E.
PY - 2013
SP - 53
EP - 61
DO - 10.5220/0004244100530061

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