Deep Learning Classification Method to Detect and Diagnose the Cancer Regions in Oral MRI Images

Authors

  • M. Praveena Kirubabai1 , G. Arumugam2

DOI:

https://doi.org/10.37506/mlu.v21i1.2353

Keywords:

Deep learning, cancer, oral images, detection system, detection rate.

Abstract

The paper proposes deep learning algorithm used to classify the oral images into either normal or abnormal
images. The cancer regions are segmented using morphological operations. The segmented cancer regions
are further diagnosed into ‘Mild’ or ‘Severe’ using deep learning algorithm. The main advantage of the deep
learning algorithm is that it requires minimum number of oral images for both classification and diagnosis
stages of the proposed work. In this paper, the total number of cancers affected oral images used is about
160 and the proposed oral cancer detection system using CNN classification approach classifies 159 cancer
affected oral images correctly and achieves 99.3% of detection rate.

Author Biography

M. Praveena Kirubabai1 , G. Arumugam2

1
Research Scholar, 2Head of the Department (Retd), Senior Professor, Madurai Kamaraj University,
Madurai-21, Tamil Nadu, India

Published

2021-01-09

How to Cite

M. Praveena Kirubabai1 , G. Arumugam2. (2021). Deep Learning Classification Method to Detect and Diagnose the Cancer Regions in Oral MRI Images. Medico Legal Update, 21(1), 462-468. https://doi.org/10.37506/mlu.v21i1.2353