Microscopy Image Processing Analaysis for Automatic Detection of Human Intestinal Parasites ALO and TTO

• Main Authors: Kamarul Hawari, Ghazali, Hadi, R. S., Zeehaida, Mohamed
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/6535/1/Microscopy_image_processing_analaysis_for_automatic_detection_of_human_intestinal_parasites_ALO_and_TTO.pdf; http://umpir.ump.edu.my/id/eprint/6535/; http://dx.doi.org/10.1109/ICECCO.2013.6718223

Parasite is an organism that lives on or in other organisms from which it obtains its' nutrients but causes harm in the process. Infection of human intestine by parasites can be due the food that we eat or the water that we drink. The most common symptoms of worm infestation include diarrhoea, stomach bloating, and digestive disorders, while other symptoms include anaemia, asthma, constipation, fatigue, low immune system, nervousness, skin rash. In a hospital, the conventional practice of diagnosing parasites infection in the human body is by manual faecal examination. Trained experts examine the faecal specimens, search for parasitic organisms, and the eggs of helminths and cysts of protozoa. If the harmful organisms are present, the sizes, shapes, numbers and sometimes colour of the organisms are examined in order to identify the species of parasites, the degree of infection and appropriate therapeutic modalities. This method of examination is inefficient when a large number of samples are involved in the examination since it poses a heavy workload, and the diagnoses rely exclusively on the experiences of the doctors and laboratory technologists. In this paper, an automatic system to diagnose human intestinal parasites using image processing technique has been proposed. A new methodology that involves the major part of image analysis such as filtering, segmentation, feature extraction and classification will be used to detect and classify intestinal parasite. A set of data has been acquired from Hospital University Sains Malaysia and has been used to test the system. Based on the result, more than 95% of accuracy was obtained for the classification of both parasites ALO and TTO.