GPU-accelerated Computed Laminography with Application to Non-destructive Testing
GPU-accelerated Computed Laminography with Application to Non-destructive Testing
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GPU 加速的计算层析成像及其在无损检测中的应用
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通讯作者：
Philipp Slusallek
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作者：
M. Maisl;L. Marsalek;C. Schorr;Jan Horacek;Philipp Slusallek
计算机断层扫描 (CT) 是医学和无损检测中非常强大的工具，但它不适合印刷电路板或纤维增强塑料板等平面物体，因为它们在扫描过程中穿透长度变化很大且空间限制很大。可以通过使用计算机断层扫描 (CL) 找到解决方案，这是一种通过斜角照射物体的技术，从而避免了 CT 中出现的问题。与现有的工业系统相比，创新的扫描仪系统 CLARA（计算机断层扫描和放射检查设备）以一种新的、高效的方式实现了这种几何形状。 CLARA 只需一根旋转轴，而不是四个平移轴，大大降低了成本和校准误差。由于有限的角度覆盖范围和特定的几何设置，CT 中使用的滤波反投影方法不能用于层压投影的重建。更灵活的迭代算法，如 SART（同时代数重建技术），为这一挑战提供了答案，并且还允许结合有关对象的先验知识来提高重建质量。这些算法的缺点在于计算要求高，导致典型的重建时间为数小时。对于某些实际应用，这可能太耗时，因此有必要加速算法。
Computed tomography (CT) is a very powerful tool in medicine and non-destructive testing but it is unsuitable for planar objects like printed circuit boards or fiber reinforced plastics sheets, due to their strongly varying penetration lengths and spatial restrictions during the scan. A solution can be found in the use of computed laminography (CL), a technique where the object is irradiated by an oblique angle, thereby circumventing the problems arising in CT. The innovative scanner system CLARA (Computed laminography and radioscopy device) realizes this geometry in a new and efficient way, compared to existing industrial systems. Instead of four translational axes, CLARA only needs one rotational axis, greatly reducing both the costs and the calibration errors. Due to the limited amount of angular coverage and the specific geometric setup, filtered back projection methods used in CT cannot be employed for the reconstruction of laminographic projections. More flexible iterative algorithms like SART (simultaneous algebraic reconstruction technique) provide an answer to this challenge and also allow to incorporate a priori knowledge about the object to increase the reconstruction quality. The drawback of these algorithms lies in their high computational demands, resulting in typical reconstruction times in the order of hours. For certain practical applications this may be too time-consuming and therefore an acceleration of the algorithms is necessary.