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Didin Yogiyansyah
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Segmentasi Citra USG (Ultrasonography) Kanker Payudara Menggunakan Fuzzy C-Means Clustering Ri Munarto; Romi Wiryadinata; Didin Yogiyansyah
Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer Vol 6, No 2 (2017): Edisi Desember 2017
Publisher : Fakultas Teknik Elektro - Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (818.928 KB) | DOI: 10.36055/setrum.v6i2.2770

Abstract

Health is a valuable treasure in survival and can be used as a parameter of quality assurance of human life. Some people even tend to ignore of health, so don’t care about the disease that will them attack and finally to death. Noted the main disease that causes death in the world is cancer. Cancer has many types, but the greatest death in each year is caused by breast cancer. Indonesia found more than 80% of cases in advanced stage, it is estimated that the incidence get 12 people from 10000 women. These numbers will to grow when there is no such treatment as prevention or early diagnosis. Growing of breast cancer patients inversely proportional to the percentage of complaints patients to doctors diagnosis in USG (Ultrasonography) breast cancer 20%. The problem is ultrasound imaging which is distorted by speckle noise. The solution is to help easier for doctors to diagnose the presence and form of breast cancer using USG. Speckle noise on USG is able to good reduce using SRAD (Speckle Reducing Anisotropic Diffusion). The filtering results are then well segmented using Fuzzy C-Means Clustering with an accuracy 91.43% of 35 samples USG image breast cancer.
Co-Authors Ri Munarto romi wiryadinata