DocumentCode :
2118618
Title :
Statistic Model of the Spine in Three-Dimension Geometry
Author :
Dai Jun ; Yu Bin ; Wang Ying
Author_Institution :
Sch. of Comput. Sci. & Technol., Xidian Univ., Xi´an, China
fYear :
2010
fDate :
24-26 Dec. 2010
Firstpage :
66
Lastpage :
70
Abstract :
The study of the statistic model of the spine in three-dimension (3-D) geometry aims to provide a scientific basis for the spine and vertebra related medical surgery. In this paper, we adopt the Active Sharpe Model (ASM) to build a spinal statistical model. That is, we first locate and mark the feature points of the three-dimensional reconstructed medical Computed Tomography images, so as to obtain the shape matrix of each spine sample. Second, we align and register the shape matrix in the sample set with Iterative Closest Point (ICP). Third, we train the samples with Principal Component Analysis (PCA) and build the spinal statistical model in 3-D geometry. Finally, we evaluate the proposed model.
Keywords :
bone; computerised tomography; geometry; image reconstruction; iterative methods; medical image processing; principal component analysis; surgery; 3-D geometry; active sharpe model; computed tomography images; iterative closest point; principal component analysis; shape matrix; spinal statistical model; three-dimension geometry; three-dimensional reconstructed medical images; vertebra related medical surgery; Active shape model; Computational modeling; Data models; Iterative closest point algorithm; Principal component analysis; Shape; Solid modeling; Active Shape Model; Principal Component Analysis; Spine; Three-dimensional Model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ISISE), 2010 International Symposium on
Conference_Location :
Shanghai
ISSN :
2160-1283
Print_ISBN :
978-1-61284-428-2
Type :
conf
DOI :
10.1109/ISISE.2010.84
Filename :
5945053
Link To Document :
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