Plasmodium detection methods in thick blood smear images for diagnosing Malaria: A review
Chyntia Raras Ajeng Widiawati, Hanung Adi Nugroho, Igi Ardiyanto · 2016
Malaria is one of the serious diseases in the world which often causes death. Based on the data from World Health Organisation (WHO) in 2015, Africa contributed 90% of death by malaria all over the world, followed by Southeast Asia and the Eastern Mediterranean. Early detection of plasmodium parasite is necessary to help the diagnose process of malaria. Nowadays, digital image processing is one of the methods used to help doctors in diagnosing a disease. In general, several stages in image processing consist of preprocessing, segmentation, feature extraction and classification. In this paper, a comparison of some image processing methods will be reviewed to determine the best method applied in this field. The confirmation is done by looking under microscope at 200 fields of view of the thick blood smear or counting of 200 to 500 of white blood cells to check the presence of the parasite. The confirmation from this research will affect the image classification result and affect the diagnosis. For the future work, look for the best method in distinguish the parasite and artifacts specially white blood cell in thick blood smear is really needed. So, can be used to count parasite density.