Title :
Multi-Modality Medical Image registration Using Support Vector Machines
Author :
Zhang, Zhao ; Zhang, Su ; Zhang, Chne-Xi ; Chen, Ya-Zhu
Author_Institution :
Inst. of Biomed. Instrum., Shanghai Jiao Tong Univ.
Abstract :
The registration of multi-modality medical images is an important tool in surgical application. We presented a method of computing different modality medical images registration of the same patient. It 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 aligning CT/MR and PET/MR scans demonstrate that it can attain sub-voxel registration accuracy. Furthermore, it is a fast registration method because support vector machine solution is sparse
Keywords :
biomedical MRI; image registration; medical image processing; positron emission tomography; support vector machines; CT; MR; PET; fast registration method; image alignment; multimodality medical image registration; prior joint intensity distribution; subvoxel registration accuracy; support vector machines; surgical application; Anatomy; Biomedical imaging; Computed tomography; Image registration; Image segmentation; Magnetic resonance imaging; Medical diagnostic imaging; Medical treatment; Positron emission tomography; Support vector machines; Joint Intensity Distribution; Multi-Modality Image Registration; Support Vector Machines;
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
DOI :
10.1109/IEMBS.2005.1615936