Affiliations: Department of Radiation Oncology, University of Texas
Southwestern Medical Center, Dallas, TX, USA
Note: [] Corresponding author: Jing Wang, Department of Radiation
Oncology, UT Southwestern Medical Center, 5641 Southwestern Medical Ave Dallas,
TX 75235-8808, USA. Tel.: +1 214 633 1741; Fax: +1 214 645 2885; E-mail:
jing.wang@utsouthwestern.edu
Abstract: BACKGROUND: High quality 4D-CBCT can be obtained by deforming a
planning CT (pCT), where the deformation vector fields (DVF) are estimated by
matching the forward projections of pCT and 4D-CBCT projections. The matching
metric used in the previous study is the sum of squared intensity differences
(SSID). The scatter signal level in CBCT projections is much higher than pCT,
the SSID metric may not lead to optimal DVF. OBJECTIVE: To improve the DVF estimation accuracy, we develop a new
matching metric that is less sensitive to the intensity level difference caused
by the scatter signal. METHODS: The negative logarithm of correlation coefficient (NLCC) is
used as the matching metric. A non-linear conjugate gradient optimization
algorithm is used to estimate the DVF. A 4D NCAT phantom and an anthropomorphic
thoracic phantom were used to evaluate the NLCC-based algorithm. RESULTS: In the NCAT phantom study, the relative reconstruction
error is reduced from 18.0% in SSID to 14.13% in NLCC. In the thoracic phantom
study, the root mean square error of the tumor motion is reduced from 1.16 mm
in SSID to 0.43 mm in NLCC. CONCLUSION: NLCC metric can improve the image reconstruction and
motion estimation accuracy of DVF-driven image reconstruction for 4D-CBCT.
Keywords: DVF estimation from projection, 4D-CBCT, DVF-driven image reconstruction
