PET-MR images registration using support vector machine

被引：0

作者：

Zhang, Z ^{[1
]}

Zhang, S ^{[1
]}

Zhang, CX ^{[1
]}

Li, Y ^{[1
]}

Chen, YZ ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Biomed Instrument Inst, Shanghai 200030, Peoples R China

来源：

PROCEEDINGS OF 2005 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-9 | 2005年

关键词：

support vector machine; density estimation; joint intensity distribution; registration;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Application of registration methods to PET and MR images is very important in diagnosis and treatment. We describe PET-MR registration method that incorporates prior joint intensity distribution between the two imaging modalities based on registered training images. The prior joint intensity distribution is modeled by support vector machine. Results demonstrate that this method is a fast registration method with sub-voxel registration accuracy.

引用

页码：3719 / 3722

页数：4

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