A Hybrid Algorithm to Address Ambiguities in Deformable Image Registration for Radiation Therapy  

作　　者：Song Gao Yongbin Zhang Jinzhong Yang Catherine H. Wang Lifei Zhang Laurence E. Court Lei Dong 

机构地区：[1]Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA [2]Scripps Proton Therapy Center, San Diego, CA, USA

出　　处：《International Journal of Medical Physics, Clinical Engineering and Radiation Oncology》2012年第2期50-59,共10页医学物理学、临床工程、放射肿瘤学（英文）

摘　　要：We proposed the use of a hybrid deformable image registration approach that combines compact-support radial basis functions (CSRBF) spline registration with intensity-based image registration. The proposed method first uses the pre-viously developed image intensity-based method to achieve voxel-by-voxel correspondences over the entire image re-gion. Next, for those areas of inaccurate registration, a sparse set of landmark correspondences was defined for local deformable image registration using a multi-step CSRBF approach. This hybrid registration takes advantage of both intensity-based method for automatic processing of entire images and the CSRBF spline method for fine adjustment over specific regions. The goal of using this hybrid registration is to locally control the quality of registration results in specific regions of interest with minimal human intervention. The major applications of this approach in radiation ther-apy are for the corrections of registration failures caused by various imaging artifacts resulting in, low image contrast, and non-correspondence situations where an object may not be imaged in both target and source images. Both synthetic and real patient data have been used to evaluate this hybrid method. We used contours mapping to validate the accuracy of this method on real patient image. Our studies demonstrated that this hybrid method could improve overall registra-tion accuracy with moderate overhead. In addition, we have also shown that the multi-step CSRBF registration proved to be more effective in handling large deformations while maintaining the smoothness of the transformation than origi-nal CSRBF.We proposed the use of a hybrid deformable image registration approach that combines compact-support radial basis functions (CSRBF) spline registration with intensity-based image registration. The proposed method first uses the pre-viously developed image intensity-based method to achieve voxel-by-voxel correspondences over the entire image re-gion. Next, for those areas of inaccurate registration, a sparse set of landmark correspondences was defined for local deformable image registration using a multi-step CSRBF approach. This hybrid registration takes advantage of both intensity-based method for automatic processing of entire images and the CSRBF spline method for fine adjustment over specific regions. The goal of using this hybrid registration is to locally control the quality of registration results in specific regions of interest with minimal human intervention. The major applications of this approach in radiation ther-apy are for the corrections of registration failures caused by various imaging artifacts resulting in, low image contrast, and non-correspondence situations where an object may not be imaged in both target and source images. Both synthetic and real patient data have been used to evaluate this hybrid method. We used contours mapping to validate the accuracy of this method on real patient image. Our studies demonstrated that this hybrid method could improve overall registra-tion accuracy with moderate overhead. In addition, we have also shown that the multi-step CSRBF registration proved to be more effective in handling large deformations while maintaining the smoothness of the transformation than origi-nal CSRBF.

关 键 词：Deformable Image REGISTRATION Radial Basis Functions SPLINE REGISTRATION IMAGE-GUIDED RADIOTHERAPY Auto-segmentation 

分 类 号：R73[医药卫生—肿瘤]