Araştırma Makalesi

Diagnosis of Breast Cancer by K-Mean Clustering and Otsu Thresholding Segmentation Methods

Cilt: 5 Sayı: 1 8 Mart 2022
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Diagnosis of Breast Cancer by K-Mean Clustering and Otsu Thresholding Segmentation Methods

Abstract

Breast cancer has increased decidedly among women. But with early diagnosis, a positive response to treatment can be given. Researchers are conducting various studies in imaging methods to detect the disease early and accurately. In this study, 9 cancerous images taken from the TCİA image data bank were detected by K-mean clustering and the Otsu threshold method. Performance metrics were evaluated by comparing them with marked reference images (ground truth) by the radiologist. For the clustering process, TPR (True Positive Rate) 0.89, FPR (False Positive Rate) 0.14, similarity 0.67, accuracy 0.87, sensitivity 0.89, exact hit ratio 0.86, specificity 0.87, F Score 0.87 were found, respectively. For Otsu, TPR (True Positive Rate) 0.84, FPR (False Positive Rate) 0.12, similarity 0.73, accuracy 0.84, sensitivity 0.84, exact hit 0.86, specificity 0.87, F Score 0.84 were calculated. The aim of this study is to determine the tumor boundaries more accurately and to use them in imaging devices in the field of health with pixel-based segmentation. As a result, both methods were successful can be used in the field and close to each other.

Keywords

Kaynakça

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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

Kaynak Göster

APA
Kuşcu, A., & Erol, H. (2022). Diagnosis of Breast Cancer by K-Mean Clustering and Otsu Thresholding Segmentation Methods. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 5(1), 258-281. https://doi.org/10.47495/okufbed.994481
AMA
1.Kuşcu A, Erol H. Diagnosis of Breast Cancer by K-Mean Clustering and Otsu Thresholding Segmentation Methods. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 2022;5(1):258-281. doi:10.47495/okufbed.994481
Chicago
Kuşcu, Aslı, ve Halil Erol. 2022. “Diagnosis of Breast Cancer by K-Mean Clustering and Otsu Thresholding Segmentation Methods”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 5 (1): 258-81. https://doi.org/10.47495/okufbed.994481.
EndNote
Kuşcu A, Erol H (01 Mart 2022) Diagnosis of Breast Cancer by K-Mean Clustering and Otsu Thresholding Segmentation Methods. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 5 1 258–281.
IEEE
[1]A. Kuşcu ve H. Erol, “Diagnosis of Breast Cancer by K-Mean Clustering and Otsu Thresholding Segmentation Methods”, Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 5, sy 1, ss. 258–281, Mar. 2022, doi: 10.47495/okufbed.994481.
ISNAD
Kuşcu, Aslı - Erol, Halil. “Diagnosis of Breast Cancer by K-Mean Clustering and Otsu Thresholding Segmentation Methods”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 5/1 (01 Mart 2022): 258-281. https://doi.org/10.47495/okufbed.994481.
JAMA
1.Kuşcu A, Erol H. Diagnosis of Breast Cancer by K-Mean Clustering and Otsu Thresholding Segmentation Methods. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 2022;5:258–281.
MLA
Kuşcu, Aslı, ve Halil Erol. “Diagnosis of Breast Cancer by K-Mean Clustering and Otsu Thresholding Segmentation Methods”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 5, sy 1, Mart 2022, ss. 258-81, doi:10.47495/okufbed.994481.
Vancouver
1.Aslı Kuşcu, Halil Erol. Diagnosis of Breast Cancer by K-Mean Clustering and Otsu Thresholding Segmentation Methods. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 01 Mart 2022;5(1):258-81. doi:10.47495/okufbed.994481

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