title: Staining pattern classification of antinuclear autoantibodies based on block segmentation in indirect immunofluorescence images.
abstract: Indirect immunofluorescence based on HEp-2 cell substrate is the most commonly used staining method for antinuclear autoantibodies associated with different types of autoimmune pathologies. The aim of this paper is to design an automatic system to identify the staining patterns based on block segmentation compared to the cell segmentation most used in previous research. Various feature descriptors and classifiers are tested and compared in the classification of the staining pattern of blocks and it is found that the technique of the combination of the local binary pattern and the k-nearest neighbor algorithm achieve the best performance. Relying on the results of block pattern classification, experiments on the whole images show that classifier fusion rules are able to identify the staining patterns of the whole well (specimen image) with a total accuracy of about 94.62%.
authors.affiliation: Department of Computer Science and Technology, Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen, China.
authors.forename: Jiaqian
authors.initials: J
authors.lastname: Li
authors.affiliation: Department of Computer Science and Technology, Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen, China.
authors.forename: Kuo-Kun
authors.initials: KK
authors.lastname: Tseng
authors.affiliation: Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan.
authors.forename: Zu Yi
authors.initials: ZY
authors.lastname: Hsieh
authors.affiliation: Computer & Communication Center, Taichung Veterans General Hospital, Taichung, Taiwan.
authors.forename: Ching Wen
authors.initials: CW
authors.lastname: Yang
authors.affiliation: Department of Mathematics, Tunghai University, Taichung, Taiwan.
authors.forename: Huang-Nan
authors.initials: HN
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D000974:Antibodies, Antinuclear / Q000276:immunology* / Q000302:isolation & purification; D001327:Autoimmune Diseases / Q000175:diagnosis* / Q000276:immunology / Q000473:pathology; D002459:Cell Fusion; D058948:Cell Tracking / Q000379:methods; D016000:Cluster Analysis; D019084:Fluorescent Antibody Technique, Indirect / Q000379:methods*; D056945:Hep G2 Cells; D006801:Humans; D007091:Image Processing, Computer-Assisted; D061848:Optical Imaging / Q000379:methods*
chemical_list: D000974:Antibodies, Antinuclear