TELKOMNIKA Telecommunication, Computing, Electronics and Control
Early detection of breast cancer using mammography images and software engineering process

TELKOMNIKA Telecommunication, Computing, Electronics and Control
Early detection of breast cancer using mammography images and software engineering process

Breast cancer, Deep-learning, Pattern recognition, Software engineering, Website design

The breast cancer has affected a wide region of women as a particular case. Therefore, different researchers have focused on the early detection of this disease to overcome it in efficient way. In this paper, an early breast cancer detection system has been proposed based on mammography images. The proposed system adopts deep-learning technique to increase the accuracy of detection. The convolutional neural network (CNN) model is considered for preparing the datasets of training and test. It is important to note that the software engineering process model has been adopted in constructing the proposed algorithm. This is to increase the reliably, flexibility and extendibility of the system. The user interfaces of the system are designed as a website used at country side general purpose (GP) health centers for early detection to the disease under lacking in specialist medical staff. The obtained results show the efficiency of the proposed system in terms of accuracy up to more than 90% and decrease the efforts of medical staff as well as helping the patients. As a conclusion, the proposed system can help patients by early detecting the breast cancer at far places from hospital and referring them to nearest specialist center.

Muayad Sadik Croock, Saja Dhyaa Khuder, Ayad Esho Korial, Sahar Salman Mahmood

DOI: 10.12928/TELKOMNIKA.v18i4.14718

Universitas Ahmad Dahlan

August 2020

Sri Wahyuni

ISSN: 1693-6930

http://journal.uad.ac.id/index.php/TELKOMNIKA

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TELKOMNIKA Telecommunication, Computing, Electronics and Control