Computer algorithm based on descriminant method for cervix cancer detection
Cervical cancer is one of the leading causes of death worldwide. This cancer is caused by a virus named Human Papilloma Virus (HPV). The HPV infections can be passed from one to another through sexual contact. Most HPV infections occur without any symptoms and go away without any treatment, but some of them can continue after many of years. That is why the cervical cancer has no symptoms unless it is already at the later stage. There is a way to detect the virus? infection, named Pap smear, where the sample is taken from woman?s cervix and then spread on the slides in order to be analyzed under a microscope. This technique is used to see the changes of the cells in the cervix. Any changes in the cell can cause cancer. The Pap smear technique depends on the eyes of a high-skilled cytologist, which can not be 100% correct due to human error. In order to prevent that, an automatic detection to read the changes of the cell is needed. This thesis provided an automatic detection of cervical cancer based on one parameter, which is the perimeter of the nucleus, by open source software named OpenCV. The classification of normal and infected cells is compared to the cell class, which is done previously, so that the result is proven correctly.
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