Publication: Classification of in Vitro Blood Stages of Plasmodium Falciparum Based on Fuzzy Inference System
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Issued Date
2018
Resource Type
File Type
application/pdf
Other identifier(s)
2-s2.0-85052295580
Rights Holder(s)
มหาวิทยาลัยศรีนครินทรวิโรฒ
Bibliographic Citation
2018 10th International Conference on Knowledge and Smart Technology: Cybernetics in the Next Decades, KST 2018. (2018), p.293-296
Suggested Citation
Tantisatirapong S., Phothisonothai M. Classification of in Vitro Blood Stages of Plasmodium Falciparum Based on Fuzzy Inference System. 2018 10th International Conference on Knowledge and Smart Technology: Cybernetics in the Next Decades, KST 2018. (2018), p.293-296. doi:10.1109/KST.2018.8426105 Retrieved from: https://hdl.handle.net/20.500.14740/3679
Author(s)
Abstract
This paper proposes the automated texture based classification of Malaria parasites in Giemsa-stained thin blood film images based on fuzzy inference system (FIS). The proposed expert and knowledge based framework includes the segmentation, feature extraction and classification of erythrocytes. First-order statistical analysis includes mean, standard deviation, skewness and kurtosis have been proposed as input parameters of FIS. The effectiveness of classifier is compared to find appropriate parame- ters for classification of normal cells and infected cells, both ring and trophozoite stages. The proposed method can provide 96.28% accuracy rate for binary classification of normal and infected cells. The results also yield 97.55% accuracy for ring stage classification, and 98.54% accuracy for trophozoite stage classification. © 2018 IEEE.
Subject(s)
Blood
Expert systems
Fuzzy systems
Higher order statistics
Image segmentation
Binary classification
Feature extraction and classification
Fuzzy inference systems
Fuzzy Inference systems (FIS)
Knowledge based framework
Plasmodium falciparum
Standard deviation
Texture based classifications
Fuzzy inference
Expert systems
Fuzzy systems
Higher order statistics
Image segmentation
Binary classification
Feature extraction and classification
Fuzzy inference systems
Fuzzy Inference systems (FIS)
Knowledge based framework
Plasmodium falciparum
Standard deviation
Texture based classifications
Fuzzy inference