Discriminative analysis of skull morphology in adolescent idiopathic scoliosis patients: Comparative study with normal controls
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摘要Statistical morphometric analysis is used in this paper to assess the skull morphological difference in adolescent idiopathic scoliosis (AIS) patients as compared with normal controls. The skull morphology analysis starts from a 3-D segmentation of the skull in MRI data using the adaptive thresholding and mathematical morphological operations. The skull vault is then separated from the whole skull surface using a demarcation plane determined by three anthropometrically meaningful landmarks. Since the segmented skull surface is not sufficiently smooth, which will introduce errors in the subsequent shape description, we devise a surface smoothing method to improve the quality of the skull surface. This mesh smoothing task is formulated as a quadratic optimization problem, in which the objective function is designed to be a linear combination of the shape term and the smoothing term, thus it overcomes the shrinkage problem in the traditional Laplacian smoothing. A spherically uniform sampling on the smoothed skull surface is per-formed afterwards. The scale-normalized distances from the skull vault centroid to the sample points are defined as features, on which the recursive feature elimination strategy is applied to select the features that contribute most to the classification of AIS patients and normal controls using the support vector machine. The results of this study quantify the skull vault surface changes and provide new evidence of bone formation abnormality in AIS patients. (c) 2008 Elsevier Ltd. All rights reserved.
著者Shi L, Wang DF, Heng PA, Wong TT, Chu WCW, Yeung BHY, Cheng JCY
期刊名稱Pattern Recognition
出版年份2008
月份9
日期1
卷號41
期次9
出版社Elsevier
頁次2800 - 2811
國際標準期刊號0031-3203
電子國際標準期刊號1873-5142
語言英式英語
關鍵詞adolescent idiopathic scoliosis; feature selection; statistical morphometric analysis; surface smoothing
Web of Science 學科類別Computer Science; Computer Science, Artificial Intelligence; COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE; Engineering; Engineering, Electrical & Electronic; ENGINEERING, ELECTRICAL & ELECTRONIC

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