Pattern Classification of Images from Acetic Acid–Based Cervical Cancer Screening: A Review

Kudva, Vidya and Prasad, Keerthana (2020) Pattern Classification of Images from Acetic Acid–Based Cervical Cancer Screening: A Review. Critical Reviews in Biomedical Engineering, 46 (2). pp. 117-133. ISSN 0278-940X

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Abstract

Automated analysis of digital cervix images acquired during visual inspection with acetic acid (VIA) is found to be of great help to physicians in diagnosing cervical cancer. Application of 3–5% acetic acid to the cervix turns abnormal lesions white, while normal lesions remain unchanged. Digital images of the cervix can be acquired during VIA procedure and can be analyzed using image-processing algorithms. Three main attributes to be considered for analysis are color, vascular patterns, and lesion margins, which differentiate between normal and abnormal lesions. This paper provides a review of state-of-the-art image analysis methods to process digital images of the cervix, acquired during VIA procedure for cervical cancer screening of classification of abnormal lesions.

Item Type: Article
Uncontrolled Keywords: Cervical cancer, image analysis, cervical cancer detection, automated cervical cancer screening, digital VIA, digital colposcopy, segmentation
Subjects: Information Sciences > MCIS Manipal
Depositing User: MIT Library
Date Deposited: 25 Jun 2020 10:12
Last Modified: 25 Jun 2020 10:12
URI: http://eprints.manipal.edu/id/eprint/155339

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