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All Journal Journal of Advanced Health Informatics Research
Deny Nughoro Triwibowo
Universitas Harapan Bangsa
Computer Science & IT Control & Systems Engineering Engineering Medicine & Pharmacology Public Health

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Identification of Breast Tumors With Image Processing Using Canny Edge Detection Deny Nughoro Triwibowo; Bala Putra Dewa; R Bagus Bambang Sumantri; Riska Suryani
Journal of Advanced Health Informatics Research Vol. 1 No. 1 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jahir.v1i1.20

Abstract

Breast tumor is one of the leading causes of death in women worldwide. The term tumor is often used for all lumps found in the human body. The increase in the number of cases of breast tumors that occur each year is due to the absence of prevention or early detection. The research was carried out by utilizing the development of information technology to create a breast tumor detection system with digital image processing. The application system will process mammogram images to detect edges with the canny method and will be classified using the SVM method. The data used is 176 data obtained from the Kaggle dataset. The test results revealed that 64 patients were classified as having malignant breast tumors (M), and 113 did not have breast tumors (B), with a classification accuracy rate of 95%. From the results obtained, the application system is very good for the early identification of breast tumors.
Co-Authors Bala Putra Dewa Bambang Sumantri, R Bagus Riska Suryani