Fast generation of digitally reconstructed radiographs using attenuation fields with application to 2D-3D image registration
Fast generation of digitally reconstructed radiographs using attenuation fields with application to 2D-3D image registration
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DOI：
10.1109/tmi.2005.856749
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发表时间：
2005-11-01
影响因子：
10.6
通讯作者：
Maurer, CR
中科院分区：
文献类型：
--
作者：
Russakoff, DB;Rohlfing, T;Maurer, CR
数字重建射线照片（DRR）的生成在计算上是昂贵的，并且通常是基于强度的二维到三维（2D-3D）配准算法的执行时间中的速率限制步骤。我们通过扩展计算机图形学领域的光场渲染技术来解决这个计算问题。光场的扩展，我们称之为衰减场（AF），允许在预处理步骤中执行大部分DRR计算;在此预计算步骤之后，DRR可以比传统的光线投射更快地生成。我们推导出表达式的物理尺寸的两个平面的AF必要的生成DRR为一个给定的X射线相机的几何形状和所有可能的对象运动在指定的范围内。由于AF是基于光线的数据结构，因此它比预先计算的DRR的巨大表具有更高的内存效率，因为它消除了复制光线的冗余。尽管如此，AF可能需要大量的内存，我们通过使用矢量量化压缩它来解决这个问题。我们比较了使用AF（AF-DRR）生成的DRR与使用射线投射（RC-DRR）生成的DRR，用于典型的C形臂几何形状和几个解剖区域的计算机断层扫描图像。它们在数量上非常相似：在所有情况下，AF-DRR与RC-DRR的峰值信噪比中值均大于43 dB。我们使用AF-DRR和RC-DRR进行基于强度的2D-3D配准，并使用来自四名患者的金标准临床脊柱图像数据评估配准精度。这两种方法的配准精度和鲁棒性几乎相同，而使用AF-DRR的执行速度要快一个数量级。
Generation of digitally reconstructed radiographs (DRRs) is computationally expensive and is typically the rate-limiting step in the execution time of intensity-based two-dimensional to three-dimensional (2D-3D) registration algorithms. We address this computational issue by extending the technique of light field rendering from the computer graphics community. The extension of light fields, which we call attenuation fields (AFs), allows most of the DRR computation to be performed in a preprocessing step; after this precomputation step, DRRs can be generated substantially faster than with conventional ray casting. We derive expressions for the physical sizes of the two planes of an AF necessary to generate DRRs for a given X-ray camera geometry and all possible object motion within a specified range. Because an AF is a ray-based data structure, it is substantially more memory efficient than a huge table of precomputed DRRs because it eliminates the redundancy of replicated rays. Nonetheless, an AF can require substantial memory, which we address by compressing it using vector quantization. We compare DRRs generated using AFs (AF-DRRs) to those generated using ray casting (RC-DRRs) for a typical C-arm geometry and computed tomography images of several anatomic regions. They are quantitatively very similar: the median peak signal-to-noise ratio of AF-DRRs versus RC-DRRs is greater than 43 dB in all cases. We perform intensity-based 2D-3D registration using AF-DRRs and RC-DRRs and evaluate registration accuracy using gold-standard clinical spine image data from four patients. The registration accuracy and robustness of the two methods is virtually identical whereas the execution speed using AF-DRRs is an order of magnitude faster.