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A review on automated diagnosis of malaria parasite in microscopic blood smears images

Authors:

Muhammad Sajjad,

Irfan MehmoodAuthors Info & Claims

Multimedia Tools and Applications, Volume 77, Issue 8

Pages 9801 - 9826

https://doi.org/10.1007/s11042-017-4495-2

Published: 01 April 2018 Publication History

Abstract

Malaria is a life-threatening disease caused by parasite of genus plasmodium, which is transmitted through the bite of infected Anopheles. A rapid and accurate diagnosis of malaria is demanded for proper treatment on time. Mostly, conventional microscopy is followed for diagnosis of malaria in developing countries, where pathologist visually inspects the stained slide under light microscope. However, conventional microscopy has occasionally proved inefficient since it is time consuming and results are difficult to reproduce. Alternate techniques for malaria diagnosis based on computer vision were proposed by several researchers. The aim of this paper is to review, analyze, categorize and address the recent developments in the area of computer aided diagnosis of malaria parasite. Research efforts in quantification of malaria infection include normalization of images, segmentation followed by features extraction and classification, which were reviewed in detail in this paper. At the end of review, the existent challenges as well as possible research perspectives were discussed.

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Cited By

Shambhu SKoundal DDas PHoang VTran-Trung KTurabieh H(2022)Computational Methods for Automated Analysis of Malaria Parasite Using Blood Smear ImagesComputational Intelligence and Neuroscience10.1155/2022/36267262022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/3626726
Sanivarapu P(2022)Adaptive tamper detection watermarking scheme for medical images in transform domainMultimedia Tools and Applications10.1007/s11042-022-12273-981:8(11605-11619)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1007/s11042-022-12273-9
Yang ZBenhabiles HHammoudi KWindal FHe RCollard D(2022)A generalized deep learning-based framework for assistance to the human malaria diagnosis from microscopic imagesNeural Computing and Applications10.1007/s00521-021-06604-434:17(14223-14238)Online publication date: 1-Sep-2022
https://dl.acm.org/doi/10.1007/s00521-021-06604-4
Show More Cited By

Index Terms

A review on automated diagnosis of malaria parasite in microscopic blood smears images
1. Applied computing
  1. Life and medical sciences
    1. Health care information systems
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems

Index terms have been assigned to the content through auto-classification.

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cover image Multimedia Tools and Applications

Multimedia Tools and Applications Volume 77, Issue 8

Apr 2018

1145 pages

ISSN:1380-7501

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Copyright © Copyright © 2018 Springer Science+Business Media, LLC, part of Springer Nature.

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Kluwer Academic Publishers

United States

Publication History

Published: 01 April 2018

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Cited By

Shambhu SKoundal DDas PHoang VTran-Trung KTurabieh H(2022)Computational Methods for Automated Analysis of Malaria Parasite Using Blood Smear ImagesComputational Intelligence and Neuroscience10.1155/2022/36267262022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/3626726
Sanivarapu P(2022)Adaptive tamper detection watermarking scheme for medical images in transform domainMultimedia Tools and Applications10.1007/s11042-022-12273-981:8(11605-11619)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1007/s11042-022-12273-9
Yang ZBenhabiles HHammoudi KWindal FHe RCollard D(2022)A generalized deep learning-based framework for assistance to the human malaria diagnosis from microscopic imagesNeural Computing and Applications10.1007/s00521-021-06604-434:17(14223-14238)Online publication date: 1-Sep-2022
https://dl.acm.org/doi/10.1007/s00521-021-06604-4
Ayas SEkinci M(2020)Microscopic image super resolution using deep convolutional neural networksMultimedia Tools and Applications10.1007/s11042-019-7397-779:21-22(15397-15415)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1007/s11042-019-7397-7
Hegde RPrasad KHebbar HSingh B(2019)Development of a robust algorithm for detection of nuclei of white blood cells in peripheral blood smear imagesMultimedia Tools and Applications10.1007/s11042-018-7107-x78:13(17879-17898)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s11042-018-7107-x

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