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Tooth Segmentation Using Gaussian Mixture Model and Genetic Algorithm

Authors
 Kim, Joo Young  ;  Yoo, Sun K.  ;  Jang, W. S.  ;  Park, Byung Eun  ;  Park, Wonse  ;  Kim, Kee Deog 
Citation
 Journal of Medical Imaging and Health Informatics, Vol.7(6) : 1271-1276, 2017 
Journal Title
 Journal of Medical Imaging and Health Informatics 
Issue Date
2017
Keywords
BIOMEDICAL ENGINEERING ; CONE BEAM CT ; CONTRAST-LIMITED ADAPTIVE HISTOGRAM EQUALIZATION ; GAUSSIAN MIXTURE MODEL ; GENETIC ALGORITHM ; TOOTH SEGMENTATION
Abstract
Background: The present study suggested an image segmentation method for dental cone beam computed tomography (CBCT) data with a proposed preprocessing step and genetic algorithm. Segmentation of dental CT images is often hampered by the proximity of teeth and alveolar bones that display similar brightness. The present study sought to overcome this difficulty by using a Gaussian mixture model (GMM) and contrast-limited adaptive histogram equalization (CLAHE) in the preprocessing step. First, the original dental image was processed by GMM to eliminate regions other than the teeth and alveolar bones. Then, we composed the preprocessed image by enhancing tooth contours through application of CLAHE. Finally, tooth and pulp regions were extracted via the evolutionary process of genetic algorithm. We confirmed that tooth segmentation using a genetic algorithm was effective in segmenting teeth that are adjacent and have similar shapes and brightness.
URI
http://ir.ymlib.yonsei.ac.kr/handle/22282913/161299
DOI
10.1166/jmihi.2017.2251
Appears in Collections:
1. Journal Papers (연구논문) > 2. College of Dentistry (치과대학) > Dept. of Advanced General Dentistry (통합치의학과)
1. Journal Papers (연구논문) > 1. College of Medicine (의과대학) > Dept. of Medical Engineering (의학공학교실)
Yonsei Authors
김기덕(Kim, Kee Deog) ; 김주영(Kim, Joo Young) ; 박원서(Park, Wonse) ; 유선국(Yoo, Sun Kook) ; 장원석(Chang, Won Seok)
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https://www.ingentaconnect.com/contentone/asp/jmihi/2017/00000007/00000006/art00022
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