Segmentasi Citra USG (Ultrasonography) Kanker Payudara Menggunakan Fuzzy C-Means Clustering

Ri Munarto, Romi Wiryadinata, Didin Yogiyansyah

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.

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References


D. T. Sarabai and K. Arthi, “Efficient Breast Cancer Classification Using Improved Fuzzy Cognitive Maps with Csonn,” Int. J. Appl. Eng. Res., vol. 11, no. 4, pp. 2478–2485, 2016.

Y. Hadiyanto, “Health First,” Rumah Sakit Pondak Indah Group, vol. 19, pp. 1–61, 2012.

O. Primadi, “Stop Kanker,” Pusat Data dan Informasi Kementerian Kesehatan RI, Jakarta, 2015.

O. Primadi, Panduan Nasional Penanganan Kanker Payudara. Jakarta: Kementerian Kesehatan RI, 2015.

D. R. Dance, S. Christofides, A. D. A. Maidment, I. D. McLean, and K. . Ng, Eds., Diagnostic Radiology Physics. Vienna: International Atomic Energy Agency, 2014.

W. Jatmiko et al., Eds., Teknik Biomedis: Teori dan Aplikasi. Depok: Fakultas Ilmu Komputer Universitas Indonesia, 2013.

I. S. Paramita, A. Makmur, and E. S. Tripriadi, “Kesesuaian Hasil Pemeriksaan Ultrasonografi dan Histopatologi pada Pasien Tumor Payudara di RSUD Arifin Achmad Periode 1 Oktober 2013 - 30 September 2014,” JOM FK, vol. 2, no. 2, pp. 1–11, 2015.

P. Sharma and J. Suji, “A Review on Image Segmentation with its Clustering Techniques,” Int. J. Signal Process. Image Process. Pattern Recognit., vol. 9, no. 5, pp. 209–218, 2016.

G. Dougherty, Digital Image Processing for Medical Applications. New York: Cambridge University Press, 2009.

H. Lutz and E. Buscarini, Eds., Manual of Diagnostic Ultrasound, 2nd ed., vol. 1. France: World Health Organization, 2011.

N. Singh, A. G. Mohaparta, B. N. Rath, and G. K. Kanungo, “GUI Based Automatic Breast Cancer Mass and Calcification Detection in Mammogram Images using K-Means & Fuzzy C-Means Methods,” Int. J. Mach. Learn. Comput., vol. 2, no. 1, pp. 7–12, 2012.

P. Sharma and J. Suji, “A Review on Image Segmentation with its Clustering Techniques,” Int. J. Signal Process. Image Process. Pattern Recognit., vol. 9, no. 5, pp. 209–218, 2016.




DOI: http://dx.doi.org/10.36055/setrum.v6i2.2770

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