International Journal of Emerging Trends in Health Sciences

International Journal of Emerging Trends in Health Sciences

Segmentation and Classification of Breast Cancer Tumour

Yazarlar: Gokalp Cinarer, Bulent Gursel Emiroglu, Ahmet Hasim Yurttakal

Cilt 2 , Sayı 1 , 2018 , Sayfalar 14-18

Konular:-

Anahtar Kelimeler:Breast Cancer,Computer-Aided Diagnosis (CAD),Magnetic Resonance Imaging (MRI)

Özet: Breast cancer is cancer that forms in the cells of the breasts. Breast cancer is the most common cancer diagnosed in women in the world. Breast cancer can occur in both men and women, but it's far more common in women. Early detection of breast cancer tumours is crucial in the treatment. In this study, we presented a computer aided diagnosis expectation maximization segmentation and co-occurrence texture features from wavelet approximation tumour image of each slice and evaluated the performance of SVM Algorithm. We tested the model on 50 patients, among them, 25 are benign and 25 malign. The 80% of the images are allocated for training and 20% of images reserved for testing. The proposed model classified 2 patients correctly with success rate of 80% in case of 5 Fold Cross-Validation 


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BibTex
KOPYALA
@article{2018, title={Segmentation and Classification of Breast Cancer Tumour}, volume={2}, number={14–18}, publisher={International Journal of Emerging Trends in Health Sciences}, author={Gokalp Cinarer, Bulent Gursel Emiroglu, Ahmet Hasim Yurttakal}, year={2018} }
APA
KOPYALA
Gokalp Cinarer, Bulent Gursel Emiroglu, Ahmet Hasim Yurttakal. (2018). Segmentation and Classification of Breast Cancer Tumour (Vol. 2). Vol. 2. International Journal of Emerging Trends in Health Sciences.
MLA
KOPYALA
Gokalp Cinarer, Bulent Gursel Emiroglu, Ahmet Hasim Yurttakal. Segmentation and Classification of Breast Cancer Tumour. no. 14–18, International Journal of Emerging Trends in Health Sciences, 2018.