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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