Data-Driven Respiratory Motion Compensation for Four-Dimensional Cone-Beam Computed Tomography (4D-CBCT) Using Groupwise Deformable Registration

Autor: Geoffrey D. Hugo, Matthew J. Riblett, Elisabeth Weiss, Gary E. Christensen
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Popis: PURPOSE: To demonstrate the feasibility of using a purely data-driven, a posteriori respiratory motion modeling and reconstruction compensation method to improve 4D-CBCT image quality under clinically relevant image acquisition conditions. METHODS: Evaluated workflows that utilized a combination of groupwise deformable image registration and motion-compensated image reconstruction algorithms. Groupwise registration is an approach that simultaneously registers all temporal frames of a 4D image to a common reference instead of one at a time so as to minimize the influence of any individual time point on the global smoothness or accuracy of the resulting deformation model. Four-dimensional Cone-Beam CT (4D-CBCT) Feldkamp-Davis-Kress (FDK) reconstructions were registered to either iteratively computed mean respiratory phase (mean-frame) or preselected respiratory phase (fixed-frame) reference images to model respiratory motion. The resulting 4D transformations were used to deform projection data during the FDK backprojection operation to create motion-compensated reconstructions. Tissue Interface Sharpness (TIS) was defined as the slope of a sigmoid curve fit to a mobile tissue boundary and was used to evaluate image quality in regions susceptible to motion artifacts. Image quality improvement was assessed for 19 clinical cases by evaluating mitigation of view-aliasing artifacts, TIS, image noise reduction, and contrast for implanted fiducial markers. RESULTS: Average (standard deviation) diaphragm TIS recovery relative to initial 4D-CBCT reconstructions was observed to be 87% (46%) using fixed-frame registration alone; 87% (47%) using fixed-frame with motion-compensated reconstruction; 101% (68%) using mean-frame registration alone; and 99% (65%) using mean-frame with motion-compensated reconstruction. Noise was reduced in sampled soft-tissue ROIs by 58% for both fixed-frame registration and registration with motion-compensation and by 57% and 58% on average for the corresponding mean-frame methods, respectively. Average improvement in local CNR was observed to be respectively 93% and 98% for fixed-frame registration and registration with motion-compensation methods and 116% and 111% for the corresponding mean-frame methods. CONCLUSION: Data-driven groupwise registration and motion-compensated reconstruction offer a feasible means of improving the quality of 4D-CBCT images acquired under clinical conditions. The addition of motion compensation reconstruction after groupwise registration visibly reduced the impact of view-aliasing artifacts for the clinical image datasets studied.
Databáze: OpenAIRE
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