Classification and comparison of malignancy detection of cervical cells based on nucleus and textural features in microscopic images of uterine cervix

Shanthi, P B and Modi, Shivani and Hareesha, K S and Kumar, Sampath (2021) Classification and comparison of malignancy detection of cervical cells based on nucleus and textural features in microscopic images of uterine cervix. International Journal of of Medical Engineering and Informatics, 13 (1). ISSN 1755-0653

[img] PDF
10923.pdf - Published Version
Restricted to Registered users only

Download (276kB) | Request a copy

Abstract

Cervical cancer is one of the major causes of death among women worldwide. Pap smear is the cytology based screening test which is used to detect abnormal cervical cells including pre-cancerous lesions. Accurate classification of Pap smear images is one of the challenging tasks in medical image processing and its performance can be enhanced by extracting and selecting the well-defined features and classifiers. The irregular chromatin structure is one of the prominent diagnostic features of abnormal cells. Classification is performed based on the extracted textural features and the benchmark Herlev dataset features. Radial basis function (RBF), polynomial and sigmoid SVM kernels are used for classification and comparison is performed with the features in benchmark database. Precision, recall and accuracy were calculated for all the combinations of the features. The classifier gives promising results when benchmark features are combined with textural features and also benchmark nucleus features with textural features. An effective integration of features for cervical cell classification had given good results for fast abnormal cell detection and primary Pap smear cell image classification.

Item Type: Article
Uncontrolled Keywords: Pap smear; cervical cancer; textural feature; GLCM; gray level co-occurrence matrix; SVM kernel
Subjects: Engineering > MIT Manipal > Computer Science and Engineering
Engineering > MIT Manipal > Electronics and Communication
Depositing User: MIT Library
Date Deposited: 29 Oct 2021 05:20
Last Modified: 29 Oct 2021 05:20
URI: http://eprints.manipal.edu/id/eprint/157547

Actions (login required)

View Item View Item