Computer Aided Diagnosis using Margin and Posterior Acoustic Featuresfor Breast Ultrasound Images

Hanung Adi Nugroho, Yuli Triyani, Made Rahmawaty, Igi Ardiyanto


Breast cancer is the most commonly diagnosed cancer among females worldwide. Computer aided diagnosis (CAD) was developed to assist radiologists in detecting and evaluating nodules so it can improve diagnostic accuracy, avoid unnecessary biopsies, reduce anxiety and control costs. This research proposes a method of CAD for breast ultrasound images based on margin and posterior acoustic features. It consists of preprocessing, segmentation using active contour without edge (ACWE) and morphological, feature extraction and classification. Texture and geometry analysis was used to determine the characteristics of the posterior acoustic and margin nodules. Support vector machines (SVM) provided better performance than multilayer perceptron (MLP). The performance of proposed method achieved the accuracy of 91.35%, sensitivity of 92.00%, specificity of 89.66%, PPV of 95.83%, NPV of 81.26% and Kappa of 0.7915. These results indicate that the developed CAD has potential to be implemented for diagnosis of breast cancer using ultrasound images.


computer aided diagnosis, ultrasonography, breast cancer, margin, posterior acoustic feature

Full Text:



Article Metrics

Abstract view : 221 times
PDF - 238 times


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus, 9th Floor, LPPI Room
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120 ext. 4902, Fax: +62 274 564604