Open Access
BIO Web Conf.
Volume 41, 2021
The 4th International Conference on Bioinformatics, Biotechnology, and Biomedical Engineering (BioMIC 2021)
Article Number 04002
Number of page(s) 5
Section Bioinformatics and Data Mining
Published online 22 December 2021
  • W. H. Organization, World malaria report 2019.. 2019. [Google Scholar]
  • H. A. Nugroho, S. A. Akbar, and E. E. H. Murhandarwati, “Feature extraction and classification for detection malaria parasites in thin blood smear, ” ICITACEE 2015. 2nd Int. Conf. Inf. Technol. Comput. Electr. Eng. Green Technol. Strength. Inf. Technol. Electr. Comput. Eng. Implementation, Proc., vol. 1, no. c, pp. 197–201, 2016. [Google Scholar]
  • A. S. Abdul Nasir, M. Y. Mashor, and Z. Mohamed, “Segmentation based approach for detection of malaria parasites using moving kmeans clustering, ” 2012 IEEE-EMBS Conf. Biomed. Eng. Sci. IECBES 2012., no. December 2012. pp. 653–658, 2012. [Google Scholar]
  • S. Kareem, I. Kale, and R. C. S. Morling, “Automated malaria parasite detection in thin blood films:-A hybrid illumination and color constancy insensitive, morphological approach, “ IEEE Asia-Pacific Conf. Circuits Syst. Proceedings, APCCAS, pp. 240–243, 2012. [Google Scholar]
  • J. Somasekar and B. Eswara Reddy, “Segmentation of erythrocytes infected with malaria parasites for the diagnosis using microscopy imaging, “ Comput. Electr. Eng., vol. 45, pp. 336–351, 2015. [Google Scholar]
  • M. Elter, E. Haßlmeyer, and T. Zerfaß, “Detection of malaria parasites in thick blood films, ” Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS, pp. 5140–5144, 2011. [Google Scholar]
  • J. E. Arco, J. M. Górriz, J. Ramírez, I. Álvarez, and C. G. Puntonet, “Digital image analysis for automatic enumeration of malaria parasites using morphological operations, “ Expert Syst. Appl., vol. 42, no. 6, pp. 3041–3047, 2015. [Google Scholar]
  • S. R. Abidin, U. Salamah, and A. S. Nugroho, “Segmentation of malaria parasite candidates from thick blood smear microphotographs image using active contour without edge, “ Proc. 2016.1st Int. Conf. Biomed. Eng. Empower. Biomed. Technol. Better Futur. IBIOMED 2016., pp. 8–13, 2016. [Google Scholar]
  • F. M. Azif, H. A. Nugroho, and S. Wibirama, “Adaptive Threshold Determination Based on Entropy in Active Contour without Edge Method for Malaria Parasite Candidate Detection, “ Proc. 2018.4th Int. Conf. Sci. Technol. ICST 2018., pp. 0–5, 2018. [Google Scholar]
  • I. R. Dave, “Image analysis for malaria parasite detection from microscopic images of thick blood smear, “ Proc. 2017.Int. Conf. Wirel. Commun. Signal Process. Networking, WiSPNET 2017., vol. 2018. Janua, pp. 1303–1307, 2017. [Google Scholar]

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