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Automatic Detection of Malaria Parasites for Estimating Parasitemia
S. S. Savkare, S. P. Narote
Pages - 310 - 315     |    Revised - 01-07-2011     |    Published - 05-08-2011
Volume - 5   Issue - 3    |    Publication Date - July / August 2011  Table of Contents
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KEYWORDS
OTSU Thresholding, Watershed Transform, Feature Extraction, SVM Classifier
ABSTRACT
Malaria parasitemia is a measurement of the amount of Malaria parasites in the patient's blood and an indicator for the degree of infection. In this paper an automatic technique is proposed for Malaria parasites detection from blood images by extracting red blood cells (RBCs) from blood image and classifying as normal or parasite infected. Manual counting of parasitemia is tedious and time consuming and need experts. Proposed automatic approach is used Otsu thresholding on gray image and green channel of the blood image for cell segmentation, watershed transform is used for separation of touching cells, color and statistical features are extracted from segmented cells and SVM binary classifier is used for classification of normal and parasite infected cells.
CITED BY (17)  
1 Razzak, I. (2015). Malarial Parasite Classification using Recurrent Neural Network. International Journal of Image Processing (IJIP), 9(2), 69.
2 DAS, D., Mukherjee, R., & Chakraborty, C. (2015). Computational microscopic imaging for malaria parasite detection: a systematic review. Journal of microscopy.
3 Razzak, M. I. (2015). Automatic Detection and Classification of Malarial Parasite. International Journal of Biometrics and Bioinformatics (IJBB), 9(1), 1.
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5 Chayadevi, M. L., & Raju, G. T. (2015). Automated Colour Segmentation of Malaria Parasite with Fuzzy and Fractal Methods. In Computational Intelligence in Data Mining-Volume 3 (pp. 53-63). Springer India.
6 Jiji, G. W., Lakshmi, V. S., Lakshmi, K. V., & Priya, S. S. (2014). Diagnosis and Prognosis of the Arbovirus-Dengue using Intelligent Algorithm. Journal of The Institution of Engineers (India): Series B, 1-6.
7 Kang, Y. J., Ha, Y. R., & Lee, S. J. (2014). Microfluidic-based measurement of erythrocyte sedimentation rate for biophysical assessment of blood in an in vivo malaria-infected mouse. Biomicrofluidics, 8(4), 044114.
8 Opoku-Ansah, J., Eghan, M. J., Anderson, B., & Boampong, J. N. (2014). Wavelength Markers for Malaria (Plasmodium Falciparum) Infected and Uninfected Red Blood Cells for Ring and Trophozoite Stages. Applied Physics Research, 6(2), p47.
9 Opoku-Ansah, J., Anderson, B., Eghan, J. M., Boampong, J. N., Adueming, P. O. W., Amuah, C. L. Y., & Akyea, A. G. (2013). Automated Protocol for Counting Malaria Parasites (P. falciparum) from Digital Microscopic Image Based on L* a* b* Colour Model and K-Means Clustering.
10 Nithyaa, A. N., Premkumar, R., Kanchana, D., & Krishnan, N. A. (2013). Automated Detection and Classification of Blood Diseases. In Recent Advancements in System Modelling Applications (pp. 393-404). Springer India.
11 Suradkar, P. T. (2013). Detection of malarial parasite in blood using image processing. International Journal of Engineering and Innovative Technology (IJEIT), 2(10).
12 Waghmare, V., & Akhter, S. Image Analysis Based System for Automatic Detection of Malarial Parasite in Blood Images.
13 Prof. S. K. Bandyopadhyay and S. Roy, “Detection of Sharp Contour of the element of the WBC and Segmentation of two leading elements like Nucleus and Cytoplasm”, International Journal of Engineering Research and Applications (IJERA), 2(1), pp.545-551, Jan-Feb 2012.
14 Bandyopadhyay, S. K., & Roy, S. (2012). Detection of sharp contour of the element of the WBC and segmentation of two leading elements like nucleus and cytoplasm. Int J Eng Res Appl (IJERA), 2(1), 545-551.
15 Crysdian, C., & Abdullah, A. H. (2012). The Application of Multi Gradient Operators to Enhance Watershed Transform for Generic Medical Segmentation. Journal of Next Generation Information Technology, 3(4).
16 Ghate, D. A., & Jadhav, C. (2012). Automatic Detection of Malaria Parasite from Blood Images. International Journal of Computer Science & Applications (TIJCSA), 1(3).
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Dr. S. S. Savkare
- India
swati_savkare@yahoo.com
Dr. S. P. Narote
- India


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