For better treatment guidance, cone-beam CT (CBCT) scans are being increasingly used in image-guided radiation therapy (IGRT). However, the applications of CBCT are greatly hampered by its poor imaging performance. In the current clinical practice, CBCT only provides patient geometry information for treatment setup. Quantitative x-ray CT images with high HU accuracy, which are particularly important for dose verification and adaptive radiation therapy, are still not achievable using CBCT. In this talk, we discuss the reasons of CBCT artifacts, and focus on the correction methods for scatter contamination, which is considered as one of the fundamental limitations of CBCT image quality. Many scatter correction algorithms have been proposed in literature, while a standard practical solution remains unclear. Our recently developed approaches are reviewed and we propose a new scatter correction method for CBCT, which is specially designed for use in the current radiation therapy. With much smaller inherent scatter signals, multi-detector CT (MDCT) obtains accurate CT images and is routinely used in the radiation treatment planning. Using the MDCT images as the “free” prior information, we estimate the scatter signals in CBCT based on an analytical model and achieve an efficient scatter correction via filtering techniques. We implement our approach on an evaluation phantom (Catphan@600), and a significant improvement is demonstrated on the scatter-corrected image. The shading and distortion artifacts are greatly suppressed, and in the selected region of interest, the reconstruction error is reduced from 33.9% to 0.7% when the proposed method is used. Future work includes further evaluation of the proposed method using anthropomorphic phantoms and patient studies.
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