Filtered Backprojection Reconstruction with Depth-Dependent Filtering.

Filtered Backprojection Reconstruction with Depth-Dependent Filtering.
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使用深度相关滤波的滤波反投影重建。

DOI:
10.1016/s1007-0214(10)70003-1
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发表时间:
2010
影响因子:
6.6
通讯作者:
Noo,Frédéric
Noo,Frédéric
中科院分区:
计算机科学2区
文献类型:
--
作者:
Dennerlein,Frank;Kunze,Holger;Noo,Frédéric

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提出了一种适用于圆形锥束计算机断层扫描(CB-CT)的直接滤波反投影(FBP)重建算法,该算法允许滤波操作在核函数具有移变带通特性的情况下有效地应用。我们的算法是从Feldkamp等人的基于斜坡滤波器的FBP方法中推导出来的,并通过将斜坡滤波分解为涉及Hilbert内核(全局操作)和随后的微分操作(局部操作)的卷积来获得。微分被实现为两个(希尔伯特滤波)数据样本的有限差分,并作为反投影步骤的一部分进行。因此,可以针对图像体积中的每个点单独地选择两个样本之间的间隔,该间隔定义滤波器操作的低通特性。在这里,我们定义的样本间距,以遵循的发散光束的几何形状的放大率,从而获得一种新的,深度相关的圆形CB-CT滤波算法。我们使用计算机模拟的CB数据评估这种算法,并证明我们的算法产生的结果,空间分辨率和图像噪声分布更均匀的视野,Feldkamp的方法相比。
A direct filtered-backprojection (FBP) reconstruction algorithm is presented for circular cone-beam computed tomography (CB-CT) that allows the filter operation to be applied efficiently with shift-variant band-pass characteristics on the kernel function. Our algorithm is derived from the ramp-filter based FBP method of Feldkamp et al. and obtained by decomposing the ramp filtering into a convolution involving the Hilbert kernel (global operation) and a subsequent differentiation operation (local operation). The differentiation is implemented as a finite difference of two (Hilbert filtered) data samples and carried out as part of the backprojection step. The spacing between the two samples, which defines the low-pass characteristics of the filter operation, can thus be selected individually for each point in the image volume. We here define the sample spacing to follow the magnification of the divergent-beam geometry and thus obtain a novel, depth-dependent filtering algorithm for circular CB-CT. We evaluate this resulting algorithm using computer-simulated CB data and demonstrate that our algorithm yields results where spatial resolution and image noise are distributed much more uniformly over the field-of-view, compared to Feldkamp's approach.
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