Automated malaria cell counter using Hough transform based method

Mohammed Harris, Bonhwa Ku, Chae Seung Lim, Hanseok Ko

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Malaria is still a threat and serious disease especially in the low income countries. Instead of the slow manual counting, an automated method of counting malaria cell should provide rapid diagnostic information to physician with online convenience. This paper proposes a circular Hough transform to detect and count the malaria cells among normal blood cells via using adaptive histogram equalization. The proposed method attains accurate and satisfying results in counting even the overlapped cells. Experimental evaluations show 96.04% average accuracy achieved for detecting malaria cells and 94.5% average accuracy for counting its ratio from the whole cells.

    Original languageEnglish
    Title of host publication2017 IEEE International Conference on Consumer Electronics, ICCE 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages404-405
    Number of pages2
    ISBN (Electronic)9781509055449
    DOIs
    Publication statusPublished - 2017 Mar 29
    Event2017 IEEE International Conference on Consumer Electronics, ICCE 2017 - Las Vegas, United States
    Duration: 2017 Jan 82017 Jan 10

    Other

    Other2017 IEEE International Conference on Consumer Electronics, ICCE 2017
    Country/TerritoryUnited States
    CityLas Vegas
    Period17/1/817/1/10

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Electrical and Electronic Engineering
    • Instrumentation

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