Contactless non-invasive method to identify abnormal tongue area using K-mean and problem identification in COVID-19 scenario
International Journal of Medical Engineering and Informatics
; 14(5):379-390, 2022.
Artigo
em Inglês
| EMBASE | ID: covidwho-2275356
ABSTRACT
Due to the spread of COVID-19 all around the world, there is a need of automatic system for primary tongue ulcer cancerous cell detection since everyone do not go to hospital due to the panic and fear of virus spread. These diseases if avoided may spread soon. So, in such a situation, there is global need of improvement in disease sensing through remote devices using non-invasive methods. Automatic tongue analysis supports the examiner to identify the problem which can be finally verified using invasive methods. In automated tongue analysis image quality, segmentation of the affected region plays an important role for disease identification. This paper proposes mobile-based image sensing and sending the image to the examiner, if examiner finds an issue in the image, the examiner may guide the user to go for further treatment. For segmentation of abnormal area, K-mean clustering is used by varying its parameters.Copyright © 2022 Inderscience Enterprises Ltd.
Texto completo:
Disponível
Coleções:
Bases de dados de organismos internacionais
Base de dados:
EMBASE
Idioma:
Inglês
Revista:
International Journal of Medical Engineering and Informatics
Ano de publicação:
2022
Tipo de documento:
Artigo
Similares
MEDLINE
...
LILACS
LIS