Early stage oral cavity cancer detection: Anisotropic pre-processing and fuzzy C-means segmentation

Zhalong Hu, Abeer Alsadoon, Paul Manoranjan, P. W.C. Prasad, Salih Ali, A. Elchouemic

Research output: Book chapter/Published conference paperConference paperpeer-review

9 Citations (Scopus)

Abstract

The high rates of oral cavity cancer incidence have been found worldwide over the past decade. The death rate from oral cavity cancer is high and increasing. This study aims to improve the tumor diagnosis accuracy in the oral cavity, duly considering image processing time. It has focused on oral Computed Tomography (CT) image pre-processing and segmentation steps to enhance image quality and clarity to improve classification result. The proposed system focused on image pre-processing and segmentation steps, using anisotropic diffusion and Fuzzy C-Means to enhance the quality of the image, then improve the accuracy of tumor detection and classification. The findings attained from the current solution are based on a proposed approach using Support Vector Machine (SVM) as the traditional machine learning method to classify the oral tumor. With the combination of the anisotropic filter and fuzzy c-means algorithm, the proposed approach achieved 90.11% accuracy, 87.5% specificity and 92.157% sensitivity rate whereas the accuracy rate of the selected current best solution is only 87.18%, This study contributes to current research mainly through the implementation of an algorithm that is able to identify small sized early tumors in image edge areas.
Original languageEnglish
Title of host publicationProceedings of the 2018 IEEE 8th Annual computing and communication workshop and conference
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages714-719
Number of pages6
ISBN (Electronic)9781538646496
ISBN (Print)9781538646502 (Print on demand)
DOIs
Publication statusPublished - 27 Feb 2018
Event8th IEEE Annual Computing and Communication Workshop and Conference: IEEE-CCWC 2018 - University of Nevada, Las Vegas, United States
Duration: 08 Jan 201810 Jan 2018
https://web.archive.org/web/20171117133749/http://ieee-ccwc.org/ (Archived page)
http://ieee-ccwc.org/ (Conference website)

Conference

Conference8th IEEE Annual Computing and Communication Workshop and Conference
Country/TerritoryUnited States
CityLas Vegas
Period08/01/1810/01/18
OtherWe are proud to present IEEE CCWC 2018 which will provide an opportunity for researchers, educators and students to discuss and exchange ideas on issues, trends, and developments in Computing and Communication. The conference aims to bring together scholars from different disciplinary backgrounds to emphasize dissemination of ongoing research in the fields of in Computing and Communication. Contributed papers are solicited describing original works in the above mentioned fields and related technologies. The conference will include a peer-reviewed program of technical sessions, special sessions, business application sessions, tutorials, and demonstration sessions. All accepted papers will be presented during the parallel sessions of the Conference and papers will be submitted for publication at IEEE Xplore Digital Library.
This conference will also promote an intense dialogue between academia and industry to bridge the gap between academic research, industry initiatives, and governmental policies. This is fostered through panel discussions, keynotes, invited talks and industry exhibits where academia is exposed to state-of-practice and results from trials and interoperability experiments. The industry in turn benefits by exposure to leading-edge research in networking as well as the opportunity to communicate with academic researchers regarding practical problems that require further research.
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