Deep convolutional neural network based HEp-2 cell classification

As different staining patterns of HEp-2 cells indicate different diseases, the classification of Indirect Immune Fluorescence (IIF) images on Human Epithelial-2 (HEp-2) cell is important for clinical applications. Different from traditional pattern recognition techniques, we use CNN to extract more high-level features for cell images classification. Compared to the existing CNN based HEp-2 classification methods, we proposed a network with deeper architecture. A class-balanced approach is also proposed to augment the HEp-2 cell dataset for network training. The proposed framework achieves an average class accuracy of 79.29% on ICPR 2012 HEp-2 dataset and a mean class accuracy of 98.26% on ICPR 2016 HEp-2 training set.

[1]  Matti Pietikäinen,et al.  HEp-2 Cell Classification via Fusing Texture and Shape Information , 2015, ArXiv.

[2]  Stephen J. McKenna,et al.  HEp-2 Cell Classification Using Multi-resolution Local Patterns and Ensemble SVMs , 2014, 2014 1st Workshop on Pattern Recognition Techniques for Indirect Immunofluorescence Images.

[3]  LinLin Shen,et al.  HEp-2 image classification using intensity order pooling based features and bag of words , 2014, Pattern Recognit..

[4]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[5]  Mario Vento,et al.  Benchmarking HEp-2 Cells Classification Methods , 2013, IEEE Transactions on Medical Imaging.

[6]  Lei Wang,et al.  HEp-2 Cell Image Classification With Deep Convolutional Neural Networks , 2015, IEEE Journal of Biomedical and Health Informatics.

[7]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[8]  Trevor Darrell,et al.  Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.

[9]  Alessia Saggese,et al.  Pattern recognition in stained HEp-2 cells: Where are we now? , 2014, Pattern Recognit..

[10]  Mario Vento,et al.  Benchmarking human epithelial type 2 interphase cells classification methods on a very large dataset , 2015, Artif. Intell. Medicine.

[11]  Alessia Saggese,et al.  HEp-2 staining pattern recognition at cell and specimen levels: Datasets, algorithms and results , 2016, Pattern Recognit. Lett..