Lee Junghoon, Labat Christian, Jain Ameet K, Song Danny Y, Burdette Everette C, Fichtinger Gabor, Prince Jerry L
Department of Electrical and Computer Eng., Johns Hopkins University, USA
Med Image Comput Comput Assist Interv. 2009;12(Pt 1):59-66. doi: 10.1007/978-3-642-04268-3_8.
In prostate brachytherapy, x-ray fluoroscopy has been used for intra-operative dosimetry to provide qualitative assessment of implant quality. More recent developments have made possible 3D localization of the implanted radioactive seeds. This is usually modeled as an assignment problem and solved by resolving the correspondence of seeds. It is, however, NP-hard, and the problem is even harder in practice due to the significant number of hidden seeds. In this paper, we propose an algorithm that can find an optimal solution from multiple projection images with hidden seeds. It solves an equivalent problem with reduced dimensional complexity, thus allowing us to find an optimal solution in polynomial time. Simulation results show the robustness of the algorithm. It was validated on 5 phantom and 18 patient datasets, successfully localizing the seeds with detection rate of > or = 97.6% and reconstruction error of < or = 1.2 mm. This is considered to be clinically excellent performance.
在前列腺近距离放射治疗中，X射线荧光透视已用于术中剂量测定，以对植入质量进行定性评估。最近的进展已使植入的放射性种子的三维定位成为可能。这通常被建模为一个分配问题，并通过解决种子的对应关系来求解。然而，它是NP难问题，并且由于大量隐藏种子的存在，在实际中该问题变得更加困难。在本文中，我们提出了一种算法，该算法可以从带有隐藏种子的多个投影图像中找到最优解。它通过降低维度复杂性来解决一个等效问题，从而使我们能够在多项式时间内找到最优解。模拟结果显示了该算法的稳健性。它在5个模型和18个患者数据集上得到验证，成功定位种子的检测率≥97.6%，重建误差≤1.2毫米。这被认为是临床上的优异表现。
