Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Indonesian Journal of Electrical Engineering and Computer Science
Azian Azamimi Abdullah
Universiti Malaysia Perlis

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Cervical cancer detection method using an improved cellular neural network (CNN) algorithm Azian Azamimi Abdullah; Aafion Fonetta Dickson Giong; Nik Adilah Hanin Zahri
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp210-218

Abstract

Cervical cancer is the second most common in Malaysia and the fourth frequent cancer among women in worldwide.  Pap smear test is often ignored although it is actually useful, beneficial and essential as screening tool for cervical cancer. However, Pap smear images have low sensitivity as well as specificity. Therefore, it is difficult to determine whether the abnormal cells are cancerous or not. Recently, computer-based algorithms are widely used in cervical cancer screening. In this study, an improved cellular neural network (CNN) algorithm is proposed as the solution to detect the cancerous cells in real-time by undergoing the image processing of Pap smear images. A few templates are combined and modified to form an ideal CNN algorithm to detect the cancerous cells in total of 115 Pap smear images. A MATLAB based CNN is developed for an automated detection of cervix cancerous cells where the templates segmented the nucleus of the cells. From the simulation results, our proposed CNN algorithm can detect the cervix cancer cells automatically with more than 88% accuracy.
Co-Authors Aafion Fonetta Dickson Giong Nik Adilah Hanin Zahri