A robust and automatic method for human parasite egg recognition in microscopic images

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• 作者：Zhixun Li ; Huiling Gong ; Wei Zhang ; Lian Chen ; Juncai Tao…
• 关键词：Automated recognition ; Image segmentation ; Human parasite eggs ; Microscopic image
• 刊名：Parasitology Research
• 出版年：2015
• 出版时间：October 2015
• 年：2015
• 卷：114
• 期：10
• 页码：3807-3813
• 全文大小：6,417 KB
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• 作者单位：Zhixun Li (1)
  Huiling Gong (1)
  Wei Zhang (1)
  Lian Chen (1)
  Juncai Tao (1)
  Langui Song (2)
  Zhongdao Wu (2)
  
  1. School of Information Engineering, Nanchang University, Nanchang, 330031, China
  2. Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510060, China
  
• 刊物类别：Biomedical and Life Sciences
• 刊物主题：Biomedicine
  Medical Microbiology
  Microbiology
  Immunology
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1432-1955

文摘

With the accelerated movement of population, human parasitoses become an increasingly serious public health’s problem. Currently, detections of parasite eggs through microscopic images are still the golden standard for diagnoses. However, this conventional method relies heavily on the experiences of inspectors, thus giving rise to misdiagnoses and missed diagnoses occasionally. And, as the number of clinical specimens increases rapidly, manual identification seems impractical. Hence, a fully automatic method is in desperate need. In this paper, we propose a robust method to segment and recognize the parasite eggs. Their contours are extracted using phase coherence technology, and the support vector machine (SVM) method based on shape and texture features is employed to classification of parasite eggs. Our novel method was comparable to the traditional method. The overall recognition rate was up to 95 %, and the overall robustness indexes, including si, fnvf, fvpf, tpvf, were 95.7, 4.9, 3.7, 95.1, respectively, suggesting that our method is effective and the robustness is good, which has great potential to become a diagnostic method in the parasitological clinic. Keywords Automated recognition Image segmentation Human parasite eggs Microscopic image