Cervical cancer is a very prevalent disease among women all over the world. Cervical cancer can form in the cervix cells found in the lower uterus. Women all over the world are at death risk as a result of this type of cancer. Cervical cancer has seven stages: normal intermediate, normal superficial, columnar, mild dysplasia, moderate dysplasia, severe dysplasia, and carcinoma in situ. Doctors in hospitals find it difficult to recognise cancer cells as it is challenging to view a nucleus through the naked eye. A normal cell’s nucleus is smaller than an abnormal cell’s nucleus. It is possible to calculate the size of the abnormal nucleus with the naked eye in order to assess the stages of cervical cancer. A tool for identifying and quantifying Pap smear cell images to detect cervical cancer has recently been suggested by several researchers. This method has the potential to increase detection and classification precision, resulting in improved results with balanced data and samples. A comprehensive study of nucleus detection cervical cancer classification techniques was conducted in this paper. As a result of the findings, the function database, detection and classification process, and device performance were all investigated for further evaluation.
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12 June 2023
THE 2ND INTERNATIONAL RECENT TRENDS IN ENGINEERING, ADVANCED COMPUTING AND TECHNOLOGY CONFERENCE (RETREAT) 2021
1–3 December 2021
Perth, Australia
Research Article|
June 12 2023
A review of detection and classification cervical cell images
Nadzirah Nahrawi;
Nadzirah Nahrawi
1
Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis (UniMAP)
, Campus Pauh Putra, 02600 Arau, Perlis, Malaysia
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Wan Azani Mustafa;
Wan Azani Mustafa
a)
1
Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis (UniMAP)
, Campus Pauh Putra, 02600 Arau, Perlis, Malaysia
2
Advanced Computing (AdvComp), Centre of Excellence (CoE), Universiti Malaysia Perlis (UniMAP)
, Campus Pauh Putra, 02600 Arau, Perlis, Malaysia
a)Corresponding author: [email protected]
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Syed Zulkarnain Syed Idrus;
Syed Zulkarnain Syed Idrus
2
Advanced Computing (AdvComp), Centre of Excellence (CoE), Universiti Malaysia Perlis (UniMAP)
, Campus Pauh Putra, 02600 Arau, Perlis, Malaysia
3
Faculty of Applied and Human Sciences, Universiti Malaysia Perlis (UniMAP)
, Jalan Alor Setar-Kangar, 01000 Kangar, Perlis, Malaysia
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Mohd Aminudin Jamlos;
Mohd Aminudin Jamlos
4
Faculty of Electronic Engineering Technology, University of Malaysia Perlis
, Campus Pauh Putra, 02600 Arau, Perlis, Malaysia
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Shahrina Ismail;
Shahrina Ismail
5
Faculty of Science and Technology, Universiti Sains Islam Malaysia (USIM)
, Bandar Baru Nilai, 71800, Negeri Sembilan, Malaysia
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Hiam Alquran;
Hiam Alquran
6
Department of Biomedical Systems and Informatics Engineering, Yarmouk University
, Irbid 21163, Jordan
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Ali Mohammad Alqudah
Ali Mohammad Alqudah
6
Department of Biomedical Systems and Informatics Engineering, Yarmouk University
, Irbid 21163, Jordan
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a)Corresponding author: [email protected]
AIP Conf. Proc. 2608, 020061 (2023)
Citation
Nadzirah Nahrawi, Wan Azani Mustafa, Syed Zulkarnain Syed Idrus, Mohd Aminudin Jamlos, Shahrina Ismail, Hiam Alquran, Ali Mohammad Alqudah; A review of detection and classification cervical cell images. AIP Conf. Proc. 12 June 2023; 2608 (1): 020061. https://doi.org/10.1063/5.0127798
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