GDL

Journal from gdlhub / 2018-01-16 09:38:43
By : Hanung Adi Nugroho, Yuli Triyani, Made Rahmawaty, Igi Ardiyanto, Telkomnika
Created : 2018-01-15, with 1 files

Keyword : Computer aided diagnosis; ultrasonography; breast cancer; margin; posterior acoustic feature
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/5021
Document Source : WEB

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 proposed a method of CAD for breast ultrasound images based on margin and posterior acoustic feature. It consisted of pre-processing, segmentation using ACWE and morphological, feature extraction and classification. Texture and geometry analysis were used to determine the characteristics of the posterior acoustic and margin nodule. 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. This results indicated that the developed CAD has potential to be implemented for diagnosis of breast cancer.

Give Comment ?#(0) | Bookmark

Property	Value
Publisher ID	gdlhub
Organization	Telkomnika
Contact Name	Herti Yani, S.Kom
Address	Jln. Jenderal Sudirman
City	Jambi
Region	Jambi
Country	Indonesia
Phone	0741-35095
Fax	0741-35093
Administrator E-mail	elibrarystikom@gmail.com
CKO E-mail	elibrarystikom@gmail.com