低剂量双能CT迭代重建及稳健PET蒙特卡洛仿真方法研究.docx

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低剂量双能CT迭代重建及稳健PET蒙特卡洛仿真方法研究
摘要：
随着医学影像技术的不断进步和应用，低剂量CT迭代重建和稳健PET蒙特卡洛仿真方法受到了广泛关注。低剂量CT迭代重建技术可以通过优化重建算法减少CT扫描剂量，降低患者辐射剂量，同时保持图像质量。稳健PET蒙特卡洛仿真方法可以提高PET成像的准确性和可重复性，以便更好地指导临床治疗。
本文首先介绍了低剂量CT迭代重建的基本原理和方法，包括高斯核函数平滑、极大似然重建和统计重建等。通过对比研究不同重建算法的效果，发现迭代重建能够在保持较高图像质量的同时降低剂量，减少伪影和噪声。同时，还介绍了一些常见的图像评价指标，如信噪比、空间分辨率和辐射剂量等，以评估重建质量。
随后，本文介绍了稳健PET蒙特卡洛仿真方法的原理和应用。蒙特卡洛方法是一种基于随机抽样的模拟方法，能够模拟PET系统的物理过程和粒子相互作用，并得到与实际PET成像结果相符合的仿真图像。稳健的PET蒙特卡洛仿真方法包括多线程技术、优化采样算法和杂质模型等，能够提高模拟图像的稳定性和准确性。
最后，本文探讨了低剂量CT迭代重建和稳健PET蒙特卡洛仿真方法的应用前景和挑战。低剂量CT迭代重建技术在临床影像学、肿瘤诊断和干预治疗等领域有着广泛的应用前景。稳健PET蒙特卡洛仿真方法可以提高PET成像的准确性，为精确治疗提供重要参考。然而，由于算法的复杂性和数值计算的难度，这些方法在实际应用中也面临一些挑战。
关键词：低剂量CT、迭代重建、稳健PET、蒙特卡洛仿真、图像质量
Abstract:
With the continuous improvement and application of medical imaging technology, low-dose CT iterative reconstruction and robust PET Monte Carlo simulation methods have received widespread attention. Low-dose CT iterative reconstruction technology can reduce CT scan dose, reduce patient radiation dose, while maintaining image quality, through optimizing reconstruction algorithms. Robust PET Monte Carlo simulation methods can improve the accuracy and repeatability of PET imaging, to better guide clinical treatment.
This paper first introduces the basic principles and methods of low-dose CT iterative reconstruction, including Gaussian kernel smoothing, maximum likelihood reconstruction, and statistical reconstruction, etc. By comparing the effects of different reconstruction algorithms, it is found that iterative reconstruction can reduce dose, reduce artifacts and noise while maintaining high image quality. In addition, some common image evaluation indices such as signal-to-noise ratio, spatial resolution, and radiation dose are introduced to evaluate the reconstruction quality.
Subsequently, this paper introduces the principles and applications of robust PET Monte Carlo simulation methods. The Monte Carlo method is a simulation method based on random sampling, which can simulate the physical processes and particle interactions of the PET system and obtain simulation images that are consistent with actual PET imaging results. Robust PET Monte Carlo simulation methods include multi-threading technology, optimized sampling algorithms, and impurity models, etc., which can improve the stability and accuracy of simulation images.
Finally, this paper discusses the application prospects and challenges of low-dose CT iterative reconstruction and robust PET Monte Carlo simulation methods. Low-dose CT iterative reconstruction technology has a wide range of applications in clinical radiology, tumor diagnosis, and intervention treatment. Robust PET Monte Carlo simulation methods can improve the accuracy of PET imaging and provide important reference for precise treatment. However, these methods also face challenges in practical applications due to the complexity of the algorithms and the difficulty of numerical calculations.
Keywords: low-dose CT, iterative reconstruction, robust PET, Monte Carlo simulation, image quality