Detection of Cervix Cancer from Pap-smear Images

Fatma Betül AKYOL; Oğuz ALTUN

doi:https://doi.org/10.35377/saucis.03.02.722670

Makale detayları

Detection of Cervix Cancer from Pap-smear Images

Yazarlar:

Fatma Betül AKYOL | Oğuz ALTUN

Ana Başlıklar:

Özel bilgisayar yöntemleri

Dergi:

Sakarya University Journal of Computer and Information Sciences 2020 Vol.3 Issue 2, pp.99-111

Belge Tipi:

Makale

Yayın Tarihi:

8/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000552042

DOI:

https://doi.org/10.35377/saucis.03.02.722670

Özet:

 

Pap-smear test is used to detect cervical cancer, which ranks fourth in the ranking of cancer diseases in women worldwide. In this study, it is aimed to design a computer based decision system that can detect cervical cancer at an early stage. Normal and abnormal cells are found in the cervix images obtained as a result of the pap-smear test and the abnormal cells are marked on the image. The features extracted from the images were examined with pathologists and a dataset was created. For each of the 917 images in the Herlev dataset, these features were extracted and stored in a dataset. Support Vector Machines (SVM), Naive Bayes, Random Forest (RF), Multilayer Perceptron (MLP), Logistic Regression (LR), K- Nearest Neighbor (KNN) methods were applied to the created dataset, and accuracy values between 83% and 92% were obtained.

Makale detayları

Detection of Cervix Cancer from Pap-smear Images

Yazarlar: Fatma Betül AKYOL | Oğuz ALTUN

Ana Başlıklar: Özel bilgisayar yöntemleri

Dergi: Sakarya University Journal of Computer and Information Sciences 2020 Vol.3 Issue 2, pp.99-111

Belge Tipi: Makale

Yayın Tarihi: 8/2020

Belge Dili: İngilizce

Document ID (Org No.): 2000552042

DOI: https://doi.org/10.35377/saucis.03.02.722670

Sayı

Yazarlar:

Fatma Betül AKYOL | Oğuz ALTUN

Ana Başlıklar:

Özel bilgisayar yöntemleri

Dergi:

Sakarya University Journal of Computer and Information Sciences 2020 Vol.3 Issue 2, pp.99-111

Belge Tipi:

Makale

Yayın Tarihi:

8/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000552042

DOI:

https://doi.org/10.35377/saucis.03.02.722670