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Shading Correction in Image Domain for Cone-Beam CT Without Prior Information

Q Fan

Q Fan*, T Niu, L Zhu, Nuclear & Radiological Engineering and Medical Physics Programs, Georgia Institute of Technology, Atlanta, GA

WE-G-217BCD-10 Wednesday 4:30:00 PM - 6:00:00 PM Room: 217BCD

Purpose: Cone-beam CT (CBCT) images contain severe shading artifacts mostly due to scatter. Many algorithms have been proposed to alleviate this problem by data correction on projections. Sophisticated methods have also been designed to further improve the image quality when prior patient information is available. In this work, we develop a novel algorithm for shading correction directly on CBCT images without any prior information.

Methods: In CBCT, projection errors (mostly scatter) result in dominant low-frequency shading artifacts in image domain. Due to circular scan geometry, these artifacts often show global or local radial patterns. We first convert the uncorrected images into the polar coordinate system. Median filtering and polynomial fitting are applied on the transformed images to accurately estimate the low-frequency bias field of shading angle-by-angle and slice-by-slice. The estimated bias field is then converted back to the Cartesian coordinate system, followed by 3D low-pass filtering to eliminate possible high-frequency components. The shading-corrected images are finally obtained as the uncorrected volume divided by the shading bias field.

Results: The proposed algorithm has been evaluated on CBCT images of a pelvis patient and a head patient. Within regions of interest, the average CBCT error is reduced from around 250 HU to 42 and 38 HU, and the spatial non-uniformity error is reduced from above 17.5% to 2.1% and 1.7% for the pelvis and the head patients, respectively. As our method suppresses only low-frequency shading artifacts, patient anatomy and contrast are well retained in the corrected images of both cases.

Conclusions: We propose an effective shading correction algorithm on CBCT images, with several advantages compared to existing approaches. The method has a high efficiency since it is deterministic and directly operates on the reconstructed images. It also requires no prior information, which facilitates its clinical use as a standard image correction solution.

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