Abstract

Clinical applications of CBCT imaging are still limited by excessive imaging dose from repeated scans and poor image quality mainly due to scatter contamination. Compressed sensing (CS) reconstruction algorithms have shown promises in recovering faithful signals from low-dose projection data, but do not serve well the needs of accurate CBCT imaging if effective scatter correction is not in place. Scatter can be accurately measured and removed using measurement-based methods. However, in conventional FDK reconstruction, these approaches are considered unpractical since they require multiple scans or moving the beam blocker during the data acquisition to compensate for the inevitable primary loss. In this work, we combine the measurement-based scatter correction and CS-based iterative reconstruction algorithm, such that scatter-free images can be obtained from low-dose data. We lower the CBCT dose by reducing the projection number and inserting lead strips between the x-ray source and the object. The insertion of lead strips also enables scatter measurement on the measured samples inside the strip shadows. CS-based iterative reconstruction is finally carried out to obtain scatter-free and low-dose CBCT images. Simulation studies are designed to optimize the lead strip geometry for a certain dose reduction ratio. After optimization, our approach reduces the CT number error from over 220HU to below 5HU on the Shepp-Logan phantom, with a dose reduction of ~80%. With the same dose reduction and the optimized method parameters, the CT number error is reduced from 242HU to 20HU in the selected region of interest on Catphan©600 phantom.

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