loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Paloma Cepeda Andrade and Sesh Commuri

Affiliation: University of Nevada, Reno, 1664 N Virginia St, Reno, NV, U.S.A.

Keyword(s): Cervical Cancer, Colposcopy, Image Segmentation, LAB Color Space, Morphological Filtering, K-means.

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 13.59.89.140

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Andrade, P. C. 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) - BIODEVICES; ISBN 978-989-758-552-4; ISSN 2184-4305, SciTePress, pages 66-73. DOI: 10.5220/0010835200003123

@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) - BIODEVICES},
year={2022},
pages={66-73},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010835200003123},
isbn={978-989-758-552-4},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - BIODEVICES
TI - Automatic Segmentation of the Cervical Region in Colposcopic Images
SN - 978-989-758-552-4
IS - 2184-4305
AU - Andrade, P.
AU - Commuri, S.
PY - 2022
SP - 66
EP - 73
DO - 10.5220/0010835200003123
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic