@inproceedings{a1a53dc1d4414f7f868f91f87b96e4c7,
title = "Positive and negative HEp-2 image classification fusing global and local features",
abstract = "Human Epithelial type 2 (HEp-2) cells play an important role in the diagnosis of autoimmune disorder. Traditional approach relies on specialists to observe HEp-2 slides via the fluorescence microscope, which suffers from a number of shortcomings like being subjective and labor intensive. Pattern recognition techniques have been recently introduced to this research issue to make the process automatic. The diagnosis includes two stages, the first stage is to classify the positive and negative cell images, the second stage is to classify the positive cells into different categories. We propose in this paper a framework using global and local features for positive and negative HEp-2 image classification. By using global feature firstly for a rough classification, cells segmentation and local feature extraction were applied further for more accurate classification. The proposed framework was evaluated with SZU dataset. The results indicate that the proposed framework can achieve as high as 98.68% accuracy.",
keywords = "HEp-2 image classification, SVM, global feature, local feature, segmentation",
author = "Jiancan Zhou and Yuexiang Li and Xiande Zhou and Linlin Shen",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017 ; Conference date: 14-10-2017 Through 16-10-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/CISP-BMEI.2017.8302196",
language = "English",
series = "Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--5",
editor = "Qingli Li and Lipo Wang and Mei Zhou and Li Sun and Song Qiu and Hongying Liu",
booktitle = "Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017",
address = "United States",
}