title: Deformable registration using edge-preserving scale space for adaptive image-guided radiation therapy.
abstract: Incorporating of daily cone-beam computer tomography (CBCT) image into online radiation therapy process can achieve adaptive image-guided radiation therapy (AIGRT). Registration of planning CT (PCT) and daily CBCT are the key issues in this process. In our work, a new multiscale deformable registration method is proposed by combining edge-preserving scale space with the multilevel free-form deformation (FFD) grids for CBCT-based AIGRT system. The edge-preserving scale space, which is able to select edges and contours of images according to their geometric size, is derived from the total variation model with the L1 norm (TV-L1). At each scale, despite the noise and contrast resolution differences between the PCT and CBCT, the selected edges and contours are sufficiently strong to drive the deformation using the FFD grid, and the edge-preserving property ensures more meaningful spatial information for mutual information (MI)-based registration. At last, the deformation fields are gained by a coarse to fine manner. Furthermore, in consideration of clinical application we designed an optimal estimation of the TV-L1 parameters by minimizing the defined offset function for automated registration. Six types of patients are studied in our work, including rectum, prostate, lung, H&N (head and neck), breast, and chest cancer patients. The experiment results demonstrate the significance of the proposed method both quantitatively with ground truth known and qualitatively with ground truth unknown. The applications for AIGRT, including adaptive deformable recontouring and redosing, and DVH (dose volume histogram) analysis in the course of radiation therapy are also studied.
authors.affiliation: College of Physics and Electronics, Shandong Normal University, Ji’nan 250014, China. lidengwang@mail.sdu.edu.cn
authors.forename: Dengwang
authors.initials: D
authors.lastname: Li
authors.forename: Hongjun
authors.initials: H
authors.lastname: Wang
authors.forename: Yong
authors.initials: Y
authors.lastname: Yin
authors.forename: Xiuying
authors.initials: X
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D005260:Female; D006258:Head and Neck Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy; D006801:Humans; D008297:Male; D011467:Prostate / Q000000981:diagnostic imaging; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results
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