Earticle

초록

영어

Malariaparasitemia is used for measuring the degree of infection by detecting the plasmodium (commonly known as the malaria parasite) in the blood of an infected patient. The most commonly used method of malarial diagnosis is counting the number of malaria-infected red blood cells in a Giemsa-stained blood smear by using a microscope. This method requires expert knowledge and is prone to inter-investigator variability. Therefore, a number of studies have been conducted on automated classification techniques that can measure malarial infection rapidly and accurately. In order to detect malaria parasites by analyzing plasmodium-infected blood smear images, conversion processing is required to make the images insensitive to the luminance contrast of microscopy and staining intensity. This paper aims to identify a grayscale conversion method optimal for plasmodium-infected blood smear images by comparing the performances of various grayscale conversion methods. The grayscale conversion methods selected for the comparison are colorimetric conversion, luma coding, conversion using the green channel only, and principal component analysis (PCA)-based conversion. We used 20 malaria-infected red blood cells and 20 normal red blood cells to compare the performances of these methods by obtaining thearea under the receiver operating curve (AUC) as the minimum histogram intra-class variance value for each cell image. With the AUC value of 0.9225, the PCA-based grayscale conversion method outperformed all other methods.

목차

Abstract
 1. Introduction
 2. Materials and Methods
  2.1. Image Acquisition
  2.2. Method Overview
  2.3. Conversion to Grayscale
  2.4. Performance Comparison
 3. Results
 4. Conclusion
 Acknowledgments
 References

키워드

저자

• JunYeon [ Department of Computer Engineering, Hallym University, Korea ]
• Jong-Dae Kim [ Department of Ubiquitous Computing, Hallym University, Korea, Bio-IT Research Center, Hallym University, Korea ]
• Chan-Young Park [ Department of Ubiquitous Computing, Hallym University, Korea, Bio-IT Research Center, Hallym University, Korea ]
• Yu-Seop Kim [ Department of Ubiquitous Computing, Hallym University, Korea, Bio-IT Research Center, Hallym University, Korea ]
• Hye-Jeong Song [ Department of Ubiquitous Computing, Hallym University, Korea, Bio-IT Research Center, Hallym University, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605