Active shape models—their training and application
Computer Vision and Image Understanding
Robust Active Shape Model Search
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
A Framework for Robust Subspace Learning
International Journal of Computer Vision - Special Issue on Computational Vision at Brown University
| Hi-index | 0.00 |
Significant research has been conducted in radiation beam gating technology to manage target and organ motions in radiotherapy treatment of cancer patients. As more and more on-board imagers are installed onto linear accelerators, fluoroscopic imaging becomes readily available at the radiation treatment stage. Thus, beam gating parameters, such as beam-on timing and beam-on window can be potentially determined by employing image registration between treatment planning CT images and fluoroscopic images. We propose a new registration method on deformable soft tissue between fluoroscopic images and DRR (Digitally Reconstructed Radiograph) images from planning CT images using active shape models. We present very promising results of our method applied to 30 clinical datasets. These preliminary results show that the method is very robust for the registration of deformable soft tissue. The proposed method can be used to determine beam-on timing and treatment window for radiation beam gating technology, and can potentially greatly improve radiation treatment quality.