Subclass Discriminant Analysis of morphological and textural features for HEp-2 staining pattern classification

PATTERN RECOGNITION

卷:47

Article

Di Cataldo, Santa¹  Bottino, Andrea¹  Ul Islam, Ihtesham¹  Vieira, Tiago Figueiredo^1,2  Ficarra, Elisa¹ 

[1] Politecn Torino, Dept Control & Comp Engn, I-10129 Turin, Italy

[2] Univ Fed Pernambuco, Dept Elect & Syst, Recife, PE, Brazil

关键词: Indirect Immunofluorescence;    Fluorescence pattern classification;    Subclass Discriminant Analysis;    Morphological analysis;    Textural analysis;   

DOI  :  10.1016/j.patcog.2013.09.024

来源: Elsevier

【 摘 要 】

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%. (C) 2013 Elsevier Ltd. All rights reserved.

【 授权许可】

Free