Image Processing Approaches for Oral Cancer Detection in Color Images

Dimensions

Amarjeet, Singh and T Ch Anil, Kumar and Tiruvedula, Mithun and Sankararao, Majji and Mooda, Rajesh and Palagati, Anusha (2022) Image Processing Approaches for Oral Cancer Detection in Color Images. 2021 5th International Conference on Electronics, Communication and Aerospace Technology (ICECA), IEEE XPLORE. pp. 817-821. ISSN 978-1-6654-3524-6

Text
56.pdf
Restricted to Registered users only
Download (3MB) | Request a copy

School: School of Core Engineering > Department of Mechanical Engineering

Department: School of Core Engineering > Department of Mechanical Engineering

Abstract

Lips, two-thirds of the tongue and inner cheek
lining are all common places for oral cancer to form. It can also
arise in hard and soft palates, pharynx, and sinuses. Head and
neck cancers are subtypes of this malignancy. Unless detected
and treated early on, oral can be dangerous. Using microscopic
biopsy images, the researchers were able to detect mouth cancer and non-cancerous lesions. Using cutting-edge techniques, it is possible to histologically diagnose oral lesions. For example, enhancing microscopic images involves transforming them from RGB to L*a*b color space, classifying the colors using k-means clustering, segmenting the nuclei, and obtaining and classifying their features.

Item Type:	Article
Subjects:	AC Rearch Cluster
Depositing User:	Unnamed user with email techsupport@mosys.org
Date Deposited:	13 Dec 2023 06:27
Last Modified:	13 Dec 2023 06:27
URI:	https://ir.vignan.ac.in/id/eprint/518

Actions (login required)

: View Item