Segmentation of dental X-ray images in medical imaging using neutrosophic orthogonal matrices
Article
Article Title | Segmentation of dental X-ray images in medical imaging using neutrosophic orthogonal matrices |
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ERA Journal ID | 17852 |
Article Category | Article |
Authors | Ali, Mumtaz (Author), Son, Le Hoang (Author), Khan, Mohsin (Author) and Tung, Nguyen Thanh (Author) |
Journal Title | Expert Systems with Applications |
Journal Citation | 91, pp. 434-441 |
Number of Pages | 8 |
Year | 2017 |
Publisher | Elsevier |
Place of Publication | United Kingdom |
ISSN | 0957-4174 |
1873-6793 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.eswa.2017.09.027 |
Web Address (URL) | http://www.sciencedirect.com/science/article/pii/S0957417417306322 |
Abstract | Over the last few decades, the advance of new technologies in computer equipment, cameras and medical devices became a starting point for the shape of medical imaging systems. Since then, many new medical devices, e.g. the X-Ray machines, computed tomography scans, magnetic resonance imaging, etc., accompanied with operational algorithms inside has contributed greatly to successful diagnose of clini- cal cases. Enhancing the accuracy of segmentation, which plays an important role in the recognition of disease patterns, has been the focus of various researches in recent years. Segmentation using advanced fuzzy clustering to handle the problems of common boundaries between clusters would tackle many challenges in medical imaging. In this paper, we propose a new fuzzy clustering algorithm based on the neutrosophic orthogonal matrices for segmentation of dental X-Ray images. This algorithm transforms image data into a neutrosophic set and computes the inner products of the cutting matrix of input. Pixels are then segmented by the orthogonal principle to form clusters. The experimental validation on real dental data sets of Hanoi Medical University Hospital, Vietnam showed the superiority of the proposed method against the relevant ones in terms of clustering quality. |
Keywords | dental X-ray image, fuzzy clustering, neutrosophic orthogonal matrices, medical diagnosis |
ANZSRC Field of Research 2020 | 490108. Operations research |
490102. Biological mathematics | |
320302. Dental materials and equipment | |
490304. Optimisation | |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | School of Agricultural, Computational and Environmental Sciences |
Vietnam National University, Vietnam | |
Abdul Wali Khan University, Pakistan | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q46zy/segmentation-of-dental-x-ray-images-in-medical-imaging-using-neutrosophic-orthogonal-matrices
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