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National Chung Hsing University Institutional Repository - NCHUIR > 理學院 > 理學院 > 依資料類型分類 > 期刊論文 >  An effective classification and numbering system for dental bitewing radiographs using teeth region and contour information

Please use this identifier to cite or link to this item: http://nchuir.lib.nchu.edu.tw/handle/309270000/133572

標題: An effective classification and numbering system for dental bitewing radiographs using teeth region and contour information
作者: Lin, P.L.;Lai, Y.H.;Huang, P.W.
關鍵字: Dental bitewing radiograph;Homomorphic filter;Homogeneity measurement;Adaptive contrast stretching;Teeth classification;Sequence alignment;Teeth numbering;x-ray images;human identification;segmentation
日期: 2010
Issue Date: 2012-12-14 10:04:12 (UTC+8)
關連: Pattern Recognition, Volume 43, Issue 4, Page(s) 1380-1392.
摘要: We propose a dental classification and numbering system to effectively segment, classify, and number teeth in dental bitewing radiographs. An image enhancement; method that combines homomorphic filtering, homogeneity-based contrast stretching, and adaptive morphological transformation is proposed to improve both contrast and illumination evenness of the radiographs simultaneously. Iterative thresholding and integral projection are adapted to isolate teeth to regions of interest (ROIs) followed by contour extraction of the tooth and the pulp (if available) from each ROI. A binary linear support vector machine using the skew-adjusted relative length/width ratios of both teeth and pulps, and crown size as features is proposed to classify each tooth to molar or premolar. Finally, a numbering scheme that combines a missing teeth detection algorithm and a simplified version of sequence alignment commonly used in bioinformatics is presented to assign each tooth a proper number. Experimental results show that our system has accuracy rates of 95.1% and 98.0% for classification and numbering, respectively, in terms of number of teeth tested, and correctly classifies and numbers the teeth in four images that were reported either misclassified or erroneously numbered, respectively. (C) 2009 Elsevier Ltd. All rights reserved.
Relation: Pattern Recognition
Appears in Collections:[依資料類型分類] 期刊論文
[依教師分類] 黃博惠
[依教師分類] 黃博惠

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