TELKOMNIKA Telecommunication, Computing, Electronics and Control
Cervical cancer diagnosis based on cytology pap smear image classification using fractional coefficient and machine learning classifiers
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Cervical cancer diagnosis based on cytology pap smear image classification using fractional coefficient and machine learning classifiers
Cervical cancer diagnosis based on cytology pap smear image classification using fractional coefficient and machine learning classifiers
Subject
Cytology image, DCT transform, Haar transform, Machine learning, Pap smear
Description
Doctors and pathologists have long been concerned about determining the malignancy from cell images. This task is laborious, time-consuming and needs expertise. Due to this reason, automated systems assist pathologists in providing a second opinion to arrive at accurate decision based on cytology images. The classification of cytology images has always been a difficult challenge among the various image analysis approaches due to its extreme intricacy. The thrust for early diagnosis of cervical cancer has always fuelled the research in medical image analysis for cancer detection. In this paper, an investigative study for the classification of cytology images is proposed. The proposed study uses the discrete coefficient transform (DCT) coefficient and Haar transform coefficients as features. These features are given as a input to seven different machine learning algorithms for normal and abnormal pap smear images classification. In order to optimize the feature size, fractional coefficients are used to form the five different sizes of feature
vectors. In the proposed work, DCT transform has given the highest
classification accuracy of 81.11%. Comparing the different machine learning algorithms the overall best performance is given by the random forest classifier.
vectors. In the proposed work, DCT transform has given the highest
classification accuracy of 81.11%. Comparing the different machine learning algorithms the overall best performance is given by the random forest classifier.
Creator
Madhura Kalbhor, Swati Vijay Shinde, Hemanth Jude
Source
DOI: 10.12928/TELKOMNIKA.v20i5.22440
Publisher
Universitas Ahmad Dahlan
Date
October 2022
Contributor
Sri Wahyuni
Rights
ISSN: 1693-6930
Relation
http://journal.uad.ac.id/index.php/TELKOMNIKA
Format
PDF
Language
English
Type
Text
Coverage
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Files
Collection
Citation
Madhura Kalbhor, Swati Vijay Shinde, Hemanth Jude, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Cervical cancer diagnosis based on cytology pap smear image classification using fractional coefficient and machine learning classifiers,” Repository Horizon University Indonesia, accessed November 21, 2024, https://repository.horizon.ac.id/items/show/4417.
Cervical cancer diagnosis based on cytology pap smear image classification using fractional coefficient and machine learning classifiers,” Repository Horizon University Indonesia, accessed November 21, 2024, https://repository.horizon.ac.id/items/show/4417.