Computer aided medical diagnosis for the identification of Malaria parasites
Interest in digital image processing methods stems from two principal application areas which comprises of improvements in pictorial information for human interpretation. This paper presents one of the applications of digital image processing in artificial intelligence particularly in the field of m...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2007
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/7131/ http://irep.iium.edu.my/7131/ http://irep.iium.edu.my/7131/ http://irep.iium.edu.my/7131/1/Siti_ICSCN_Malaria_2007.pdf |
| Summary: | Interest in digital image processing methods stems from two principal application areas which comprises of improvements in pictorial information for human interpretation. This paper presents one of the applications of digital image processing in artificial intelligence particularly in the field of medical diagnosis system. Currently in Malaysia the traditional method for the identification of Malaria parasites requires a trained technologist to manually examine and detect the number of the parasites subsequently by reading the slides. This is a very time consuming process, causes operator fatigue and is prone to human errors and inconsistency. An automated system is therefore needed to complete as much work as possible for the identification of Malaria parasites. Digitized microscopic images of thin blood smear specimens are used in this project. The endeavor is to develop a software where the end user can use a computer aided medical diagnosis system via graphical user interface whereby the number of existed Malaria parasites will be counted. The technique used is Digital Image Processing whilst the main programming language used is C++ programming which permits portability of the program so as to provide easy future software expansion. The integration both soft computing tools in this project has been successfully designed with the capability to improve the quality of the image, analyze and classify the image as well as calculating the number of Malaria parasites. |
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