A Recent Systematic Review of Cervical Cancer Diagnosis: Detection and Classification

Authors

  • Wan Azani Mustafa Advanced Computing (AdvCOMP), Centre of Excellence, Universiti Malaysia Perlis (UniMAP), Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
  • Nur Ain Alias Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia
  • Mohd Aminuddin Jamlos Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia
  • Shahrina Ismail Faculty of Science and Technology, Universiti Sains Islam Malaysia (USIM), Bandar Baru Nilai, Negeri Sembilan, 71800, Malaysia
  • Hiam Alquran Department of Biomedical Systems and Informatics Engineering, Yarmouk University 556, Irbid 21163, Jordan

DOI:

https://doi.org/10.37934/araset.28.1.8196

Keywords:

Cervical, cancer, detection and classification

Abstract

Women around the world are frequently diagnosed with cervical cancer. In the beginning, there were no symptoms for the fourth most common cause of fatality in women. Cells of cervical cancer develop gradually at the cervix. Several studies have mentioned that the initial detection of cervical tumours is essential for cancer to be properly treated and to make sure cancer can be successfully treated while minimizing deaths due to cervical cancer. The diagnosis of such cancer before it spreads fast is currently a pressing issue for healthcare professionals. This also provides an extensive understanding with respect to the physical characteristics of the healthy and unhealthy cervix and aids in early treatment planning by giving detailed information about one another. Utilizing image segmentation, several techniques are employed to find malignancy. The dataset contains four distinct pathological pictures, including normal, malignancy, and high-grade squamous intraepithelial lesions (HSIL). While pap tests are the most popular way to diagnose cervical cancer, their accuracy depends a lot on how well cytotechnicians can use brightfield microscopy to spot abnormal cells on smears.

Author Biographies

Wan Azani Mustafa, Advanced Computing (AdvCOMP), Centre of Excellence, Universiti Malaysia Perlis (UniMAP), Pauh Putra Campus, 02600 Arau, Perlis, Malaysia

azani.mustafa@gmail.com

Nur Ain Alias, Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia

ainalias@studentmail.unimap.edu.my

Mohd Aminuddin Jamlos, Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia

mohdaminudin@unimap.edu.my

Shahrina Ismail, Faculty of Science and Technology, Universiti Sains Islam Malaysia (USIM), Bandar Baru Nilai, Negeri Sembilan, 71800, Malaysia

shahrinaismail@usim.edu.my

Hiam Alquran, Department of Biomedical Systems and Informatics Engineering, Yarmouk University 556, Irbid 21163, Jordan

heyam.q@yu.edu.jo

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Published

2022-09-20

How to Cite

Wan Azani Mustafa, Nur Ain Alias, Mohd Aminuddin Jamlos, Shahrina Ismail, & Hiam Alquran. (2022). A Recent Systematic Review of Cervical Cancer Diagnosis: Detection and Classification. Journal of Advanced Research in Applied Sciences and Engineering Technology, 28(1), 81–96. https://doi.org/10.37934/araset.28.1.8196

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