An automated pattern recognition system for classifying indirect immunofluorescence images of HEp-2 cells and specimens
作者：
Highlights：
• We propose systems for classifying immunofluorescence images of HEp-2 cells.
• Images are classified at both the cell level and the specimen level.
• Ensemble SVM classification based on sparse coding of texture features was effective.
• Cell pyramids and artificial dataset augmentation increased mean class accuracy.
• The proposed systems came first in the I3A contest associated with ICPR 2014.
摘要
Highlights•We propose systems for classifying immunofluorescence images of HEp-2 cells.•Images are classified at both the cell level and the specimen level.•Ensemble SVM classification based on sparse coding of texture features was effective.•Cell pyramids and artificial dataset augmentation increased mean class accuracy.•The proposed systems came first in the I3A contest associated with ICPR 2014.
论文关键词：Anti-nuclear antibody test,Cell classification,Subcellular fluorescence patterns,HEp-2 cells,Multi-resolution local patterns,Ensemble SVM
论文评审过程：Received 21 January 2015, Revised 15 July 2015, Accepted 5 September 2015, Available online 28 September 2015, Version of Record 27 November 2015.
论文官网地址：https://doi.org/10.1016/j.patcog.2015.09.015
