NDLI: Plasmodium vivax classification from digitalization microscopic thick blood film using combination of second order statistical feature extraction and K-Nearest Neighbor (K-NN) classifier method

Content Provider	IEEE Xplore Digital Library
Author	Rahmanti, Farah Zakiyah Sutojo Novita Kurnia Ningrum Niken Kartika Imania Purnomo, Mauridhi Hery
Copyright Year	2015
Description	Author affiliation: Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia (Purnomo, Mauridhi Hery) \|\| Department of Informatics Engineering, University of Dian Nuswantoro, Semarang, Indonesia (Rahmanti, Farah Zakiyah; Sutojo; Novita Kurnia Ningrum; Niken Kartika Imania)
Abstract	Malaria disease is one of the most serious public health problem in various tropical countries, included in Indonesia. Data of The Ministry of Health mentioned that Papua, West Papua, and NTT (Nusa Tenggara Timur) are provinces which have the greatest cases of malaria. With high mortality rate, malaria need to be treated as quick as possible. Therefore, the accurate and timely diagnosis of malaria infection is essential to control and to cure the disease. We propose an accurate method to classify plasmodium vivax from digitalization microscopic thick blood film using combination of second order statistic feature extraction and K-Nearest Neighbor (K-NN) classifier method. In this feature extraction, we use GLCM (Gray Level Co-occurrence Matrix) to get contrasts, correlations, energys, and homogeneity values. Those values will be inserted in classification module as an input. We use K-NN classifier method to classify the red blood film are infected by plasmodium vivax or not. This process can also classify plasmodium vivax into thropozoit, schizont, and gametocytes. Based on the result of experiments, the combination of second order statistical and K-NN has a high accuracy for classifying plasmodium vivax with average accuracy 95%.
Starting Page	79
Ending Page	83
File Size	290481
Page Count	5
File Format	PDF
e-ISBN	9781467378000
DOI	10.1109/ICICI-BME.2015.7401339
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-02
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Correlation Films Microscopy Malaria Plasmodium Vivax Feature extraction K-Nearest Neighbor Second Order Statistical Thick Blood Film Yttrium Blood Diseases
Content Type	Text
Resource Type	Article

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