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Parasite and Infected-Erythrocyte Image Segmentation in Stained Blood Smears

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Abstract

Identifying parasite species and their stage is very important in scrutinizing the properties of malaria, and preventing as well as diagnosing it. Unfortunately, it is a labor-intensive and time-consuming task. Moreover, the diagnosis accuracy heavily depends on the experience and skill of the technician, whose training is expensive. Developing a computer-aided system is thus necessary for identifying parasite species and their stage for malaria diagnosis. Extracting the infected erythrocytes and parasites from a blood smear image is essential for such as system. The present study proposes an automatic malaria parasite detector for segmenting parasites and malaria-infected erythrocytes from a blood smear image. This detector can objectively and efficiently help a doctor diagnose malaria. Experimental results show that the proposed detector performs well in segmenting parasites and malaria-infected erythrocytes from a blood smear image taken under a microscope.

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Author's contributions

YKC and KCT conceived the study. YKC designed the approach and performed the computational analysis with YWH, CLW, CMW, LYT, CWL, and KCT. YKC and KCT supervised the work and tested the program. YWH, CMW, LYT, and CWL wrote the manuscript. KCT prepared the samples and collected the data together with YWH and CLW. YKC and KCT contributed analyzing experimental studies. All authors read and approved the final manuscript. YKC and KCT contributed equally and are the correspondent authors as well as listed in alphabetical order.

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Authors and Affiliations

  1. Department of Veterinary Medicine, National Chung Hsing University, Taichung, 40227, Taiwan, ROC

    Yi-Wen Hung & Kwong-Chung Tung

  2. Department of Information Management, National Chin-Yi University of Technology, Taichung, 41170, Taiwan, ROC

    Ching-Lin Wang

  3. Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung, 41170, Taiwan, ROC

    Chuin-Mu Wang

  4. Department of Management Information Systems, National Chung Hsing University, Taichung, 40227, Taiwan, ROC

    Yung-Kuan Chan

  5. Institute of Networking and Multimedia, National Chung Hsing University, Taichung, 40227, Taiwan, ROC

    Lin-Yu Tseng & Chiu-Wen Lee

Authors
  1. Yi-Wen Hung
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  2. Ching-Lin Wang
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  3. Chuin-Mu Wang
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  4. Yung-Kuan Chan
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  5. Lin-Yu Tseng
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  6. Chiu-Wen Lee
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  7. Kwong-Chung Tung
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Corresponding authors

Correspondence to Yung-Kuan Chan or Kwong-Chung Tung.

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Hung, YW., Wang, CL., Wang, CM. et al. Parasite and Infected-Erythrocyte Image Segmentation in Stained Blood Smears. J. Med. Biol. Eng. 35, 803–815 (2015). https://doi.org/10.1007/s40846-015-0101-0

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  • DOI: https://doi.org/10.1007/s40846-015-0101-0

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