Automatic Segmentation of the Cervical Region in Colposcopic Images

Paloma Cepeda Andrade, Sesh Commuri

2022

Abstract

Cervical cancer is one of the most common cancers affecting women, especially in developing countries and in resource constrained areas in the western world. While easily treatable if detected early, the lack of adequate resources and skilled physicians make this disease difficult to detect and treat. In this paper, we propose a vision-based approach anchored in machine-learning principles to detect and quantify lesions on the surface of the cervix. Preliminary results indicate that the proposed method can segment images of the cervix and successfully detect lesions other artifacts. The image normalization approach can also determine the locations of lesions and their spread. Validation of this approach during clinical trials is being pursued as the first step towards developing low-cost bioinformatics-based screening tools for early detection of cervical cancer.

Paper Citation

in Harvard Style

Andrade P. and Commuri S. (2022). Automatic Segmentation of the Cervical Region in Colposcopic Images. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 1: BIODEVICES; ISBN 978-989-758-552-4, SciTePress, pages 66-73. DOI: 10.5220/0010835200003123

in Bibtex Style

@conference{biodevices22,
author={Paloma Cepeda Andrade and Sesh Commuri},
title={Automatic Segmentation of the Cervical Region in Colposcopic Images},
booktitle={Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 1: BIODEVICES},
year={2022},
pages={66-73},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010835200003123},
isbn={978-989-758-552-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 1: BIODEVICES
TI - Automatic Segmentation of the Cervical Region in Colposcopic Images
SN - 978-989-758-552-4
AU - Andrade P.
AU - Commuri S.
PY - 2022
SP - 66
EP - 73
DO - 10.5220/0010835200003123
PB - SciTePress