Cervical cancer afflicts women worldwide. The patients’ mortality with cancer has been increased by changing to
westernized dietary habit and lifestyle. In order to detect early cervical cancer, a liquid-based cytology (LBC) was used
to examine the exfoliated cells collected from the cervix. This procedure helps to decrease the mortality rate. However,
this test mostly involves manual examination by the pathologists. This procedure needs to develop more efficient tool
in detecting cervical cancer which rate kept increasing. As such, this study was designed to develop some methods to
increase the effectiveness of LBC. The diagnosis algorithm was also established to diagnose the processed cell images
via an imaging process algorithm based on the diagnosis criteria. A cell diagnosis program based on GUI, combined
with the imaging process and the diagnosis algorithms were developed to automate the test process. The results of this
studies showed that this new program can be used for effective diagnosis of cervical cancer. Moreover, it was deemed
to increase the precision and accuracy of diagnosis and save patient time.