Diagnosis of Breast Cancer by K-Mean Clustering and Otsu Thresholding Segmentation Methods
Abstract
Keywords
Kaynakça
- [1] Cancer Facts and Figures. American Cancer Society. Atlanta 2020; 1–76.
- [2] Canadian Cancer Statistics Advisory Committee. Canadian Cancer Statistics 2018.
- [3] Toronto ON: Canadian Cancer Society 2020. Available at: cancer.ca/Canadian-Cancer-Statistics-2018-EN.
- [4] Sun L., Legood R., Sadique Z. Dos-Santos-Silva I., Yang L. Cost–effectiveness of risk-based breast cancer screening programme China. Bull World Health Organ 2018; 96: 568-577.
- [5] Malvia S., Bagadi SA., Dubey US., Saxena S. Epidemiology of breast cancer in Indian women. Asia-Pacific J Clin Oncol 2017; 13(4): 289–295. [6] Ng EYK., Kee EC. Advanced integrated technique in breast cancer thermography. J Med Eng Technol 2008; 32: 103–114.
- [7] Mentari BA., Rasyid Y., Fitri A., Khairul M. Histogram statistics and GLCM features of breast thermograms for early cancer detection, 15th International Conference on Electrical Engineering/Electronics. Computer, Telecommunications and Information Technology (ECTI-NCON2018) 2018; 120- 124.
- [8] Etehadtavakol M., Ng EYK. Survey of numerical bioheat transfer modelling for accurate skin surface measurements. Therm Sci Eng Prog J 2020; 20: 2451–9049.
- [9] Das S., Abraham A., Konar A. Automatic clustering using an ımproved differential evolution algorithm. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 2008; 38: 218-237.
Ayrıntılar
Birincil Dil
İngilizce
Konular
Elektrik Mühendisliği
Bölüm
Araştırma Makalesi
Yayımlanma Tarihi
8 Mart 2022
Gönderilme Tarihi
12 Eylül 2021
Kabul Tarihi
20 Aralık 2021
Yayımlandığı Sayı
Yıl 2022 Cilt: 5 Sayı: 1
Cited By
Remote Sensing Change Detection Based on Unsupervised Multi-Attention Slow Feature Analysis
Remote Sensing
https://doi.org/10.3390/rs14122834
