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Practical interior tomography with radial Hilbert filtering and a priori knowledge in a small round area

机译:实用的内部层析成像,具有径向希尔伯特滤波功能,并且在较小的圆形区域中具有先验知识

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Purposes: Interior tomography problem can be solved using the so-called differentiated backprojection-projection onto convex sets (DBP-POCS) method, which requires a priori knowledge within a small area interior to the region of interest (ROI) to be imaged. In theory, the small area wherein the a priori knowledge is required can be in any shape, but most of the existing implementations carry out the Hilbert filtering either horizontally or vertically, leading to a vertical or horizontal strip that may be across a large area in the object. In this work, we implement a practical DBP-POCS method with radial Hilbert filtering and thus the small area with the a priori knowledge can be roughly round (e.g., a sinus or ventricles among other anatomic cavities in human or animal body). We also conduct an experimental evaluation to verify the performance of this practical implementation. Methods: We specifically re-derive the reconstruction formula in the DBP-POCS fashion with radial Hilbert filtering to assure that only a small round area with the a priori knowledge be needed (namely radial DBP-POCS method henceforth). The performance of the practical DBP-POCS method with radial Hilbert filtering and a priori knowledge in a small round area is evaluated with projection data of the standard and modified Shepp-Logan phantoms simulated by computer, followed by a verification using real projection data acquired by a computed tomography (CT) scanner. Results: The preliminary performance study shows that, if a priori knowledge in a small round area is available, the radial DBP-POCS method can solve the interior tomography problem in a more practical way at high accuracy. Conclusions: In comparison to the implementations of DBP-POCS method demanding the a priori knowledge in horizontal or vertical strip, the radial DBP-POCS method requires the a priori knowledge within a small round area only. Such a relaxed requirement on the availability of a priori knowledge can be readily met in practice, because a variety of small round areas (e.g., air-filled sinuses or fluid-filled ventricles among other anatomic cavities) exist in human or animal body. Therefore, the radial DBP-POCS method with a priori knowledge in a small round area is more feasible in clinical and preclinical practice.
机译:目的:内部层析成像问题可以使用所谓的差分反投影-凸集投影(DBP-POCS)方法解决,该方法需要在要成像的感兴趣区域内部的小区域内具有先验知识。从理论上讲,需要先验知识的小区域可以是任何形状,但是大多数现有实现都是水平或垂直执行希尔伯特滤波,从而导致垂直或水平条带可能会跨越较大的区域。物体。在这项工作中,我们实现了带有径向希尔伯特滤波的实用DBP-POCS方法,因此具有先验知识的小区域可以大致呈圆形(例如,人或动物体内的其他解剖腔中的窦或心室)。我们还进行了实验评估,以验证此实际实施的性能。方法:我们特别采用径向希尔伯特滤波以DBP-POCS方式重新推导重建公式,以确保只需要具有先验知识的小圆形区域(此后称为径向DBP-POCS方法)。使用标准Hilbert幻影模型和修改后的Shepp-Logan幻影模型的投影数据,评估了在小圆形区域内采用径向希尔伯特滤波和先验知识的实用DBP-POCS方法的性能,然后使用通过获得的真实投影数据进行验证计算机断层扫描(CT)扫描仪。结果:初步性能研究表明,如果可以在较小的圆形区域中获得先验知识,则放射状DBP-POCS方法可以更实际,更准确地解决内部层析成像问题。结论:与需要水平或垂直条带先验知识的DBP-POCS方法的实现方式相比,径向DBP-POCS方法仅需要在较小的圆形区域内获得先验知识。在实践中可以容易地满足对先验知识的获得的这种宽松要求,因为在人或动物体内存在各种小的圆形区域(例如,充满空气的鼻窦或充满液体的心室以及其他解剖腔)。因此,在较小的圆形区域中具有先验知识的放射状DBP-POCS方法在临床和临床前实践中更为可行。

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