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Plasmodium life cycle stage classification based quantification of malaria parasitaemia in thin blood smears.

Abbas, N, Saba, T, Rehman, A, Mehmood, Z, Kolivand, H, Uddin, M and Anjum, A (2018) Plasmodium life cycle stage classification based quantification of malaria parasitaemia in thin blood smears. Microscopy Research and Technique. ISSN 1097-0029

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Abstract

Visual inspection for the quantification of malaria parasitaemiain (MP) and classification of life cycle stage are hard and time taking. Even though, automated techniques for the quantification of MP and their classification are reported in the literature. However, either reported techniques are imperfect or cannot deal with special issues such as anemia and hemoglobinopathies due to clumps of red blood cells (RBCs). The focus of the current work is to examine the thin blood smear microscopic images stained with Giemsa by digital image processing techniques, grading MP on independent factors (RBCs morphology) and classification of its life cycle stage. For the classification of the life cycle of malaria parasite the k-nearest neighbor, Naïve Bayes and multi-class support vector machine are employed for classification based on histograms of oriented gradients and local binary pattern features. The proposed methodology is based on inductive technique, segment malaria parasites through the adaptive machine learning techniques. The quantification accuracy of RBCs is enhanced; RBCs clumps are split by analysis of concavity regions for focal points. Further, classification of infected and non-infected RBCs has been made to grade MP precisely. The training and testing of the proposed approach on benchmark dataset with respect to ground truth data, yield 96.75% MP sensitivity and 94.59% specificity. Additionally, the proposed approach addresses the process with independent factors (RBCs morphology). Finally, it is an economical solution for MP grading in immense testing.

Item Type: Article
Additional Information: This is the peer reviewed version of the following article: Abbas N, Saba T, Rehman A, et al. Plasmodium life cycle stage classification based quantification of malaria parasitaemia in thin blood smears. Microsc Res Tech. 2018;1–13, which has been published in final form at https://dx.doi.org/10.1002/jemt.23170. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
Uncontrolled Keywords: 0299 Other Physical Sciences, 0601 Biochemistry and Cell Biology, 0912 Materials Engineering
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RM Therapeutics. Pharmacology
Divisions: Computer Science
Publisher: Wiley
Related URLs:
Date Deposited: 28 Jan 2019 11:11
Last Modified: 28 Jan 2019 13:28
DOI or Identification number: 10.1002/jemt.23170
URI: http://researchonline.ljmu.ac.uk/id/eprint/10043

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