多能散射模型融合的定量锥形束CT重建
Quantitative cone-beam CT reconstruction with polyenergetic scatter model fusion
摘要：
由于锥束CT（CBCT）的视场大，散射是造成其测量误差的主要原因，散射的复杂性使其补偿困难。迭代多能重建算法提供了在CT中提供定量成像的潜力，但它们通常与散射污染的测量不兼容。在这项工作中，我们引入了一个多能卷积散射模型，该模型直接融合到重建过程中，并利用在每次迭代时易于获得的信息，以节省一小部分额外的计算成本。我们评估这种方法与数值和真实CBCT测量，并显示出显着增强的电子密度估计和伪影减轻预先计算的快速自适应散射核叠加（fASKS）。我们证明了我们的方法有两个层次的好处：减少重建前估计散射所引入的偏差;适应样本的光谱和空间特性。
英文摘要：
Scatter can account for large errors in cone-beam CT (CBCT) due to its wide field of view, and its complicated nature makes its compensation difficult. Iterative polyenergetic reconstruction algorithms offer the potential to provide quantitative imaging in CT, but they are usually incompatible with scatter contaminated measurements. In this work, we introduce a polyenergetic convolutional scatter model that is directly fused into the reconstruction process, and exploits information readily available at each iteration for a fraction of additional computational cost. We evaluate this method with numerical and real CBCT measurements, and show significantly enhanced electron density estimation and artifact mitigation over pre-calculated fast adaptive scatter kernel superposition (fASKS). We demonstrate our approach has two levels of benefit: reducing the bias introduced by estimating scatter prior to reconstruction; and adapting to the spectral and spatial properties of the specimen.
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