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《Computer Engineering and Applications》 2004-24
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3-D Matching Interpolation Based on Images Segmentation

Zou Pengcheng Yin Xuesong(Institute of VR and Multimedia,Hangzhou Inst.of Electronics Engineering,Hangzhou310037)  
Dose calculation in radiotherapy needs equal spacing3D images data sets,which can be reconstructed from a sequence of cross-sectional slices(such as CT,MRI etc).Typically,the spacing between slices is greater than the spacing between points on a slice.To get equal sample spacing in all directions,one usually uses grey-baed interpola-tion method.Unfortunately,grey-baed interpolation makes the images blurred on edge.Another usually uses shape-based interpolation that doesn't get the data of whole image.In order to solve the problem,the paper introduces a new interpo-lation algorithm based on images segmentation.Firstly,the algorithm obtains the area of air,soft tissue and skeleton through segmenting images.Then,the algorithm uses matching interpolation in the same density areas and scales the size of area as the interpolation data in the different density area.So that the new image basically satisfies the requirements of medical image interpolation.Compared with linear interpolation,the new algorithm improves the quality of image.The interpolation can be effectively used to construct3D volume models.
【CateGory Index】: TP391.41
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