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A Patch-based CBCT Scatter Artifact Correction Using Prior CT

机译:使用先前的CT的基于补丁的CBCT散布伪像校正

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摘要

We have developed a novel patch-based cone beam CT (CBCT) artifact correction method based on prior CT images. First, we used the image registration to align the planning CT with the CBCT to reduce the geometry difference between the two images. Then, we brought the planning CT-based prior information into the Bayesian deconvolution framework to perform the CBCT scatter artifact correction based on patch-wise nonlocal mean strategy. We evaluated the proposed correction method using a Catphan phantom with multiple inserts based on contrast-to-noise ratios (CNR) and signal-to-noise ratios (SNR), and the image spatial non-uniformity (ISN). All values of CNR SNR and ISN in the corrected CBCT image were much closer to those in the planning CT images. The results demonstrated that the proposed CT-guided correction method could significantly reduce scatter artifacts and improve the image quality. This method has great potential to correct CBCT images allowing its use in adaptive radiotherapy.
机译:我们已经开发了一种基于以前的CT图像的基于补丁的新型锥束CT(CBCT)伪影校正方法。首先,我们使用图像配准将计划CT与CBCT对齐,以减小两个图像之间的几何差异。然后,我们将基于计划的基于CT的先验信息引入贝叶斯反卷积框架中,以基于逐块非局部均值策略执​​行CBCT散射伪影校正。我们基于对比度噪声比(CNR)和信噪比(SNR)以及图像空间不均匀度(ISN),使用带有多个插入物的Catphan体模评估了提出的校正方法。校正后的CBCT图像中CNR SNR和ISN的所有值都非常接近计划CT图像中的所有值。结果表明,所提出的CT引导校正方法可以显着减少散射伪影并提高图像质量。该方法具有校正CBCT图像的巨大潜力,可用于适应性放射治疗。

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