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Reliable identification of Human Epithelial-2 (HEp-2) cell patterns can facilitate the diagnosis of systemic autoimmune diseases. However, traditional approach requires experienced experts to manually recognize the cell patterns, which suffers from the inter-observer variability. In this paper, an automatic pattern recognition system using fully convolutional network (FCN) was proposed to simultaneously...
Reliable automatic system for Human Epithelial-2 (HEp-2) cell image classification can facilitate the diagnosis of systemic autoimmune diseases. In this paper, an automatic pattern recognition system using fully convolutional network (FCN) was proposed to address the HEp-2 specimen classification problem. The FCN in the proposed framework was adapted from VGG-16, which was trained with ICPR 2016 dataset...
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...
The patterns of Human Epithelial type 2 (HEp-2) cell provide useful information for the diagnosis of systemic autoimmune diseases. However, the recognition of cell patterns requires manual annotation by experienced physicians, which is subject to inter-observer variability. Therefore, an automatic diagnosis system is desirable. As the crucial pre-processing step for cell pattern recognition, the performance...
We proposed in this paper an accurate and efficient approach for palmprint identification. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where LBP is then applied to code the relation among the magnitude of wavelet response at central pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. In...
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