- author = "I. Ketut Eddy Purnama and Farah Zakiyah Rahmanti and Mauridhi Hery Purnomo",
- booktitle = "3rd International Conference on Instrumentation, Communications, Information Technology, and Biomedical Engineering (ICICI-BME 2013)",
- title = "Malaria parasite identification on thick blood film using genetic programming",
- year = "2013",
- month = "7-8 " # nov,
- pages = "194--198",
- address = "Bandung",
- keywords = "genetic algorithms, genetic programming, Thick Blood Film, Malaria Parasite, Feature Extraction, Receiver Operating Characteristics, ROC",
-
DOI = "
doi:10.1109/ICICI-BME.2013.6698491",
- size = "5 pages",
- abstract = "Thin blood film is used to know type and phase of the malaria parasite, but which is widely used in Indonesia is the thick blood film. Therefore we need a method that can identify parasites in thick blood film image with a high percentage of accuracy. This research aims to establish a more objective classification system and reduce the subjective factors of medical personnel in diagnosing the type of malaria parasite include its phase. It has three main stages, there are preprocessing, feature extraction, and classification. Preprocessing aims to eliminate the noise, feature extraction using red-green-blue channel colour histogram, hue channel HSV histogram, and hue channel HSI histogram, classification using Genetic Programming to identify parasites and also to detect type and phase of the parasite. Experiment was conducted on 180 thick blood film images that classified into two classes. The classification has an average accuracy of 95.49percent for non-parasites and 95.58percent for parasites. Meanwhile when system is used to classified into six classes, testing result have an average accuracy of 90.25percent not parasites, 82.25percent vivax thropozoit, 75.83percent vivax schizont, 81.75percent vivax gametocytes, 90.75percent falciparum thropozoit, 86.75percent falciparum gametocytes. This research confirm that identifying malaria parasite in thick blood film is possible.",
-
notes = "Indonesia, DSLR Camera. 25 features, pop 100,
learning the images Does not give evolved formulae. Also known as \cite{6698491}",
