The sinogram inpainting based methods such as normalized metal artifact reduction (NMAR) shows good performance in reducing the metal artifacts. However, these methods wipe away the structures near the metal which are severely corrupted by artifacts. The proposed method using a weight to lower metal corrupted pixels during the iteration instead of using an inpainting method to conserve the structures. Then, the proposed method was complementarily used with NMAR to generate a corrected image using the frequency split method. The titanium inserted XCAT phantoms were simulated from the 80kVp of energy. The metals were segmented from the filtered backprojection image using the threshold from the projection data. Afterwards, they were projected to acquire the metal sinogram index and the metal subtracted projection data. A weight map is generated from the scale factor and the log of the original raw data which has the metal index. The metal subtracted projection data were iteratively reconstructed. During the iteration, the step size of the update term was affected by a weight map, and the contributions of the metal present sinogram were lowered. Finally, using the frequency split approach, the corrected image was generated from the proposed and NMAR results. It was possible to lower the artifacts while conserving the structures in the proposed method. This work indicates the weighted iterative reconstruction can be complementarily used with the existing FSMAR approach.
This work proposed a motion detection method for cone-beam computed tomography (CBCT) that utilizes a calibration
phantom of known geometry as the motion detector and an established geometric calibration protocol to provide the
motion information. An initial numerical study regarding the consequences of motion and its correction was conducted
with a Shepp-Logan and an XCAT phantom. Motion artifacts were induced by acquiring the projections in a simple
saddle trajectory scan. Since the scanning trajectory is set, the magnitude of motion for each projection view is already
known, the correction of motion can then be efficiently implemented. Motion correction was done prior to the
backprojection process of the filtered backprojection (FBP) image reconstruction algorithm. Results showed that motion
correction improved the image quality of the reconstructed images. For a known or unknown scanning trajectory, the
geometric calibration method can define the geometric information of a scanning system. In the current work,
projections of a calibration phantom of known geometry were acquired from a saddle trajectory scan, and geometric
parameters for selected projection views were successfully computed from the projection matrix provided by the
geometric calibration method. Further studies will involve an experimental investigation wherein a calibration phantom
is attached to a randomly moving object and scanned in a circular trajectory. Utilizing the parameters extracted from the
geometric calibration, an accurate description of the object motion can be used and adapted for motion correction.
In this work, we proposed a novel scatter correction method for a circular cone-beam computed tomography (CBCT)
using a hardware-based approach that completes both data acquisition and scatter correction in a single rotation. We
utilized (quasi-)redundancy in the circular cone-beam data, and applied the chord-based backprojection-filtration (BPF)
algorithm to avoid the problem of filtering discontinuous data that would occur if conventional filtered-backprojection
(FBP) algorithms were used. A single scan was performed on a cylindrical uniform phantom with beam-block strips
between the source and the phantom, and the scatter was estimated for each projection from the data under the blocked
regions. The beam-block strips (BBSs) were aligned parallel to the rotation axis, and the spacing between the strips was
determined so that the data within the spaces constitute at least slightly more than the minimum data required for image
reconstruction. The results showed that the image error due to scatter (about 30 % of the attenuation coefficient value) has
been successfully corrected by the proposed algorithm.
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