Classifying HEp-2 fluorescence patterns in Indirect Immunofluorescence (IIF) HEp-2 cell imaging is important for the differential diagnosis of autoimmune diseases. The current technique, based on human visual inspection, is time-consuming, subjective and dependent on the operator's experience. Automating this process may be a solution to these limitations, making IIF faster and more reliable. This work proposes a classification approach based on Subclass Discriminant Analysis (SDA), a dimensionality reduction technique that provides an effective representation of the cells in the feature space, suitably coping with the high within-class variance typical of HEp-2 cell patterns. In order to generate an adequate characterization of the fluorescence patterns, we investigate the individual and combined contributions of several image attributes, showing that the integration of morphological, global and local textural features is the most suited for this purpose. The proposed approach provides an accuracy of the staining pattern classification of about 90%.

Subclass Discriminant Analysis of Morphological and Textural Features for HEp-2 Staining Pattern Classification / DI CATALDO, Santa; Bottino, ANDREA GIUSEPPE; UL-ISLAM, Ihtesham; FIGUEIREDO VIEIRA, Tiago; Ficarra, Elisa. - In: PATTERN RECOGNITION. - ISSN 0031-3203. - 47:7(2014), pp. 2389-2399. [10.1016/j.patcog.2013.09.024]

Subclass Discriminant Analysis of Morphological and Textural Features for HEp-2 Staining Pattern Classification

FICARRA, ELISA
2014

Abstract

Classifying HEp-2 fluorescence patterns in Indirect Immunofluorescence (IIF) HEp-2 cell imaging is important for the differential diagnosis of autoimmune diseases. The current technique, based on human visual inspection, is time-consuming, subjective and dependent on the operator's experience. Automating this process may be a solution to these limitations, making IIF faster and more reliable. This work proposes a classification approach based on Subclass Discriminant Analysis (SDA), a dimensionality reduction technique that provides an effective representation of the cells in the feature space, suitably coping with the high within-class variance typical of HEp-2 cell patterns. In order to generate an adequate characterization of the fluorescence patterns, we investigate the individual and combined contributions of several image attributes, showing that the integration of morphological, global and local textural features is the most suited for this purpose. The proposed approach provides an accuracy of the staining pattern classification of about 90%.
2014
47
7
2389
2399
Subclass Discriminant Analysis of Morphological and Textural Features for HEp-2 Staining Pattern Classification / DI CATALDO, Santa; Bottino, ANDREA GIUSEPPE; UL-ISLAM, Ihtesham; FIGUEIREDO VIEIRA, Tiago; Ficarra, Elisa. - In: PATTERN RECOGNITION. - ISSN 0031-3203. - 47:7(2014), pp. 2389-2399. [10.1016/j.patcog.2013.09.024]
DI CATALDO, Santa; Bottino, ANDREA GIUSEPPE; UL-ISLAM, Ihtesham; FIGUEIREDO VIEIRA, Tiago; Ficarra, Elisa
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1240347
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