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《Chinese Journal of Scientific Instrument》 2012-06
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Subvoxel-accuracy surface detection method based on contour pre-segmentation for computed tomography images

Zha Fanglong,Zhang Dinghua,Huang Kuidong,Zhang Liang,Li Mingjun(Key Laboratory of Contemporary Design and Integrated Manufacturing Technology,Ministry of Education, Northwestern Polytechnical University,Xi'an 710072,China)  
Aiming at the precision and integrity problems of point cloud extraction in the detecting applications based on computed tomography(CT) images,this paper proposes a pre-segmentation based subvoxel-accuracy surface detection method with fine integrity and high precision.Firstly,the Otsu segment algorithm is adopted to obtain the initial sets of voxel-accuracy contour points for the CT image.With these sets as the coarse positioning contour,the complete region of interest(ROI) for subvoxel-accuracy surface detection is adaptively generated.Then,a surface voxel judging criterion is put forward based on non-maximum gradient suppression strategy,which avoids the gradient threshold selection dilemma.Finally,the positions of the subvoxel-accuracy surface points are determined based on 3D Facet model.Experiment results indicate that our method has a significant promotion in overcoming the contour loss and severe pseudo edges.The total positioning precision could be less than 0.2 voxels,and it could also obtain a computational speedup ratio above 3 compared with conventional methods.
【Fund】: 国家科技重大专项(2012ZX04007-021);; 国家自然科学基金(51105315);; 西北工业大学种子基金(Z2011080)资助项目
【CateGory Index】: TP391.41
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