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Title

Automated Cervical Cancer Detection using Level Set segmentation and Two-Level Cascade Classification

Year: 1398
COI: ICNS04_052
Language: EnglishView: 245
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Authors

Mohamad Elyasi Ghopi - Department of Computer Engineering, Shahid Chamran University, Ahwaz, Iran
Mahsa Hedayati - Department of Computer Engineering, Islamic Azad University, Tabriz Branch, Iran

Abstract:

Pap smear test has been broadly used for detection of cervical cancer. Cervical cancer ranks as the fourth most prevalent cancer affecting women worldwide and its early detection provides the opportunity to help save life. To that end, automated diagnosis and classification of cervical cancer from pap-smear images has become a necessity as it enables accurate, reliable and timely analysis of the condition’s progress. So this paper proposes a method for automatic cervical cancer detection using cervical cell segmentation and classification. In this paper, the Herlev dataset, which consists of 7 classes, is used. A single cervical cell image is segmented into cytoplasm and nucleus using Level Set method. We first proposed 24 features, including morphologic and texture features, based on the characteristics of each cell type. We then used a two-level cascade integration system of two classifiers to classify the cervical cells into normal and abnormal cells. In the first step, C4.5 is used to classify the cells into 7 different classes and in the second step Logistic Regression classify cells into normal and abnormal cells. The experiments show that the overall results of the proposed two-level classification are better than the SVM and ANN single classifiers.

Keywords:

pap smear test, cervical cancer, Level Set method, cascade classifier

Paper COI Code

This Paper COI Code is ICNS04_052. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/883867/

How to Cite to This Paper:

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Elyasi Ghopi, Mohamad and Hedayati, Mahsa,1398,Automated Cervical Cancer Detection using Level Set segmentation and Two-Level Cascade Classification,?th International Conference on Natural Sciences (ICNS????)-Mathematics & Computer,Sanandaj,,,https://civilica.com/doc/883867

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Type of center: دانشگاه دولتی
Paper count: 15,140
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