Positive and negative HEp-2 image classification fusing global and local features

Jiancan Zhou, Yuexiang Li, Xiande Zhou, Linlin Shen

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017
EditorsSong Qiu, Hongying Liu, Li Sun, Lipo Wang, Qingli Li, Mei Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781538619377
DOIs
Publication statusPublished - 22 Feb 2018
Externally publishedYes
Event10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017 - Shanghai, China
Duration: 14 Oct 201716 Oct 2017

Publication series

NameProceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017
Volume2018-January

Conference

Conference10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017
Country/TerritoryChina
CityShanghai
Period14/10/1716/10/17

Keywords

  • global feature
  • HEp-2 image classification
  • local feature
  • segmentation
  • SVM

ASJC Scopus subject areas

  • Health Informatics
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering

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