C-arm cone-beam CT (CBCT) is adopted rapidly for imaging-guidance in interventional and surgical procedures. However, measured CBCT data are truncated often due to the limited detector size especially in the presence of additional interventional devices outside the imaging field of view (FOV). In our previous work, it has been demonstrated that a constrained optimization-based reconstruction with an additional data-derivative fidelity term can effectively suppress the truncation artifacts. In this work, in attempt to evaluate the optimization-based reconstruction, two task-relevant metrics, are proposed for characterization of the recovery of the low-contrast objects and the reduction of streak artifacts. Results demonstrate that the optimization program and the associated CP algorithms can significantly reduce streak artifacts, leading to improved visualization of lowcontrast structures in the reconstruction relative to clinical FDK reconstruction.
Dan Xia, Yu-Bing Chang, Adnan H. Siddiqui, Zheng Zhang, Joe Manak, Emil Y. Sidky, and Xiaochuan Pan, "Artifacts reduction in low-contrast neurological imaging with C-arm system," Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 105731S (Presented at SPIE Medical Imaging: February 15, 2018; Published: 9 March 2018); https://doi.org/10.1117/12.2293629.
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