Design and Implementation of Non-Invasive Malaria Detection System

Osman, Mohammed; Salih, Hassan; Salih, Osama A.; Abdalaah, Nazar; Khider, Mohamed

doi:10.1109/iccceee.2018.8515878

Cited by 1 publication

(1 citation statement)

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“…(v) A technique that different authors use to diagnose malaria is invasive, in which an injection syringe takes a blood sample. Therefore, there is a requirement for a noninvasive technique that can be used to detect malaria [ 128 ]. (vi) After the analysis of Table 7 , it has been found that all the existing state-of-the-art techniques used to detect malaria from microscopic blood smear images are not very accurate.…”

Section: Discussionmentioning

confidence: 99%

Computational Methods for Automated Analysis of Malaria Parasite Using Blood Smear Images: Recent Advances

Shambhu

Koundal

Das

et al. 2022

Computational Intelligence and Neuroscience

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Malaria comes under one of the dangerous diseases in many countries. It is the primary reason for most of the causalities across the world. It is presently rated as a significant cause of the high mortality rate worldwide compared with other diseases that can be reduced significantly by its earlier detection. Therefore, to facilitate the early detection/diagnosis of malaria to reduce the mortality rate, an automated computational method is required with a high accuracy rate. This study is a solid starting point for researchers who want to look into automated blood smear analysis to detect malaria. In this paper, a comprehensive review of different computer-assisted techniques has been outlined as follows: (i) acquisition of image dataset, (ii) preprocessing, (iii) segmentation of RBC, and (iv) feature extraction and selection, and (v) classification for the detection of malaria parasites using blood smear images. This study will be helpful for: (i) researchers can inspect and improve the existing computational methods for early diagnosis of malaria with a high accuracy rate that may further reduce the interobserver and intra-observer variations; (ii) microbiologists to take the second opinion from the automated computational methods for effective diagnosis of malaria; and (iii) finally, several issues remain addressed, and future work has also been discussed in this work.

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Section: Discussionmentioning

confidence: 99%