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Evaluation of reconstruction algorithms for triple head coincidence imaging by hot sphere detectability

机译:热球可检测性重建算法的重建算法

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Simulations and measurements of triple head PET acquisitions of a hot sphere phantom were performed to evaluate the performance of two different reconstruction algorithms (projection based ML-EM and listmode ML-EM)for triple head gamma camera coincidence systems. A geometric simulator assuming a detector with 100 percent detection efficiency and only detection of trues was used. The resolution was equal to the camera system. The measurements were performed with a triple headed gamma camera. Simulated and measured data were stored in listmode format, which allowed the flexibility for different reconstruction algorithms. As a measure for the performance the hot spot detectability was taken because tumor imaging is the most important clinical application for gamma camera coincidence systems. The detectability was evaluated by calculating the recovered contrast and the contrast-to-noise ratio. Results show a slightly improved contrast but a clearly higher contrast-to-noise ratio for list mode reconstruction.
机译:进行了热球幻影的三头宠物采集的模拟和测量,以评估三个不同的重建算法(投影基于ML-EM和ListMode ML-EM)的性能,用于三重伽马相机巧合系统。使用具有100%检测效率的检测器的几何模拟器和仅检测迹象。分辨率等于相机系统。用三圈伽马相机进行测量。模拟和测量数据以ListMode格式存储,这允许不同的重建算法的灵活性。作为性能的措施,采取了热点可检测性,因为肿瘤成像是伽马相机重合系统最重要的临床应用。通过计算回收的对比度和对比度与噪声比来评估可检测性。结果表明对比度略有提高,但清单模式重建的对比度较高。

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