文章基本信息

标题：Malaria Parasite Detection using Various Machine Learning Algorithms and Image Processing
其他标题：English
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作者：Yash Panchori ; Nikita Agarwal ; Aashiya Singhal 等
期刊名称：International Journal of Computer Science and Engineering
印刷版ISSN：2278-9960
电子版ISSN：2278-9979
出版年度：2020
卷号：7
期号：2
页码：68-70
DOI：10.14445/23488387/IJCSE-V7I2P108
出版社：IASET Journals
摘要：Malaria is mosquito-borne blood disease caused by protozoan parasites of the genus Plasmodium. The Conventional diagnostic tool for malaria is the examination of a stained blood cell of a patient in microscope which is time consuming and dependent on the experience of a pathologist. In this project, an improved image processing system along with different machine learning algorithms for detection of parasites is proposed. On implementation we found the accuracy of the model varying from 85% to 90% for different algorithms. This model has increased the efficiency of malaria parasite detection and minimizes the human intervention during the detection process.
关键词：machine learning; image processing; malaria; Gaussian blur; classification; contour; regression