Bilateral filtering based sliding motion compensated 4D-CBCT: a simulation study
10.13491/j.issn.1004-714X.2021.03.005
- VernacularTitle:基于双边滤波的滑动运动补偿4D-CBCT仿真成像研究
- Author:
Tao YOU
1
;
Chunmei LI
2
;
Chunhua DAI
1
;
Deyu CHEN
1
;
Jun DANG
3
Author Information
1. The Affiliated Hospital of Jiangsu University, Zhenjiang 212001 China.
2. The Fourth Division Hospital of Xinjiang Production and Construction Corps, Yili 835000 China.
3. Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, Shenzhen 518116 China.
- Publication Type:DiagnosisandTreatment/OriginalArticles
- Keywords:
Sliding Motion;
Bilateral Filtering;
4D-CBCT;
Deformable Vector Fields;
Simultaneous Reconstruction
- From:
Chinese Journal of Radiological Health
2021;30(3):269-275
- CountryChina
- Language:Chinese
-
Abstract:
Objective This study reconstructed 4D-CBCT for fully automatic compensated sliding motion by incorporating the bilateral filtering into the Deformable Vector Field (DVF). Methods First, a motion compensated simultaneous algebraic reconstruction technique (Modified Simultaneous Algebra Reconstruction Technique, mSART) was used to generate a high quality reference phase by using all phase projection stogether with the initial 4D-DVFs, which were generated via Demons registration between 0% phase and each other phaseimage. The 4D-DVF was optimized by matching the forward projection of the deformed 0% phase with the measured projection of the target phase. The loss function’s DVF smoothing constrain term contained bilateral filtering kernel that contained: 1) an spatial domain Guassian kernel; 2) animage intensity domain Guassian kernel; and 3) a DVF domain Guassian kernel. By choosing suitable kernel variances, the sliding motion can be extracted. A non-linear conjugate gradient optimizer wasused. We validated the algorithm on a Non-Uniform Rotational B- spline based Cardiac-Torso (NCAT) phantom. Quantification was evaluated by: 1) the Root-Mean-Square-Error (RMSE) together with the Maximum-Error (MaxE); 2) the Dice coefficient of the extracted lung contour from the final reconstructed images and 3) the relative reconstruction error (RE) to evaluate the algorithm's performance. Results The motion trajectory's RMSE/MaxEare 0.796/1.02 mm for bilateral filtering reconstruction; and 2.704/4.08 mm for original reconstruction. Image content such a stherib position, the hearted gedefinition, the fibrous structures all had been better corrected with bilateral filtering. Conclusion We developed a bilateral filtering based fully automatic sliding motion compensated 4D-CBCT scheme. Digital phantom study confirmed the improved motion estimation and image reconstruction ability. It can be used as a 4D-CBCT image guidance tool for lung SBRTtreatment.
