A Novel Method to Detect and Classify Oral Cavity Cancer System
R Prabhakaran1, J Mohana2

1R Prabhakaran*, Research Scholar, Saveetha School of Engineering, SIMATS, Chennai, India.
2J Mohana, Associate Professor, Saveetha School of Engineering, SIMATS, Chennai, India.

Manuscript received on November 15, 2019. | Revised Manuscript received on 20 November, 2019. | Manuscript published on December 10, 2019. | PP: 3883-3887 | Volume-9 Issue-2, December 2019. | Retrieval Number: A4013119119/2019©BEIESP | DOI: 10.35940/ijitee.B7763.129219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The primary objective of this article is to build a Computer Aided Diagnostic (CAD) technique for the segmentation of Oral cavity cancer. The frequency of oral cancer occurrence has been observed globally in recent decades. The death ratio from oral cancers is excessive and keeps on rising. This article has concentrated on oral Computed Tomography (CT) image pre-processing and segmentation techniques to enhance resolution of the image and readability to enhance classification outcome. The proposed model targeted on image pre-processing and segmentation steps to improve the resolution of the image, then enhance the precision of swelling recognition and classification. The American Cancer Society calculates that there will be almost 60,000 new patients and roughly 9,000 deaths from oral or throat cancer in 2017. The preliminary prediction of oral cancer is to check out the ocular areas cautiously and record the holes present in the teeth of the damaged person as true-color digital images. The choice about the extra cure of the oral cancer damaged person is principally based on the growth of the lesion. Oral cancers are a type of cancer, the place few irregular wounds or patches will present in the holes present in the teeth. As it is challenging to recognize it in the beginning states, it has one of the bad survival ratios. The suggested method receives the Computerized Tomography (CT) scanned images of the cancer damaged vicinity and can detect the presence of malignancy. The managing of oral cancer is a multidisciplinary attempt, as every damaged person provides the treating clinicians with a sole collection of difficulties, the managing of which affects on each living and high- condition of life. 
Keywords: Object Segmentation, Object Detection, Oral Disease, Cancer.
Scope of the Article: Classification