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Spatially-variant image-based modeling of PSF deformations with application to a limited angle geometry from a dual-panel breast-PET imager

机译:从双面母乳宠物成像仪应用于有限角几何的PSF变形的基于空间变体的图像模型

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ABSTRACT: Dual-panel PET system configuration can lead to spatially variable point-spread functions (PSF) of considerable deformations due to depth-of-interaction effects and limited angular coverage. If not modelled properly, these effects result in decreased and inconsistent recovery of lesion activity across the field-of-view (FOV), as well as mispositioning of lesions in the reconstructed image caused by strong PSF asymmetries. We implemented and evaluated models of such PSF deformations with spatially-variant image-based resolution modeling (IRM) within reconstruction (varRM) using the Direct Image REConstruction for Time-of-flight (DIRECT) method and within post-reconstruction deconvolution methods. In addition, DIRECT reconstruction was performed with a spatially-invariant IRM (invRM) and without resolution modeling (noRM) for comparison. The methods were evaluated using simulated data for a realistic breast model with a set of 5 mm lesions located throughout the FOV of a dual-panel Breast-PET scanner. We simulated high-count data to focus on the ability of each method to correctly recover the PSF deformations, and a clinically realistic count level to assess the impact of low count data on the quantitative performance of the evaluated techniques. Performance of the methods evaluated herein was assessed by comparing lesion activity recovery (%BIAS), consistency (%SD) across the FOV, overall error (%RMSE), and recovery of each lesion location. As expected, all techniques using IRM provide considerable improvement over the noRM reconstruction. For the high-count cases, the overall quantitative performance of all IRM techniques, whether within reconstruction or within post-reconstruction, is similar if the lesion location misplacements are ignored. However, invRM provides less consistent performance on activity across lesions and is not able to recover accurate lesion locations. For a clinically realistic count level, varRM reconstruction consistently outperforms all compared approaches, while the post-reconstruction IRM approaches exhibit higher %SD and %RMSE values due to being more affected by the data noise than the within-reconstruction IRM approaches. ?2019 Institute of Physics and Engineering in Medicine.
机译:摘要:由于互动深度效应和有限的角度覆盖,双面板PET系统配置可以导致相当变形的空间可变点传播功能(PSF)。如果未正确建模,这些效果导致在视野(FOV)上的病变活动的降低和不一致的恢复,以及由强的PSF不对称引起的重建图像中的病变失去定位。我们利用直接图像重建在重建(直接)方法和重建后的解卷积方法中,在重建(VARRM)内实现和评估了这种PSF变形的模型,其基于基于空间的基于图像的分辨率建模(IRM)。此外,使用空间 - 不变的IRM(INVRM)和没有分辨率建模(NORM)进行直接重建进行比较。使用模拟数据进行评估,用于逼真的乳房模型,该模型,位于双面板母乳扫描仪的整个FOV中,一组5毫米病变。我们模拟了高计数数据,专注于每种方法正确恢复PSF变形的能力,以及临床上现实的计数水平,以评估低计数数据对评估技术的定量性能的影响。通过将病变活动恢复(%偏差),总体误差(%RMSE)和恢复每个病变位置进行评估,通过将病变活动恢复(%偏差),一致性(%SD)和恢复来评估本文评估的方法的性能。如预期的那样,使用IRM的所有技术对规范重建提供了相当大的改进。对于高计数案例,如果忽略病变位置错位,所有IRM技术的整体定量性能,无论是在重建中是否在重建中都是相似的。但是,INVRM在跨病变的活动提供了不一致的性能,并且无法恢复准确的病变位置。对于临床实际计数水平,VARRM重建始终如一地优于所有比较的方法,而重建后IRM方法呈现出更高的%SD和%RMSE值,因为由于数据噪声比重建IRM方法更大。 ?2019年医学物理与工程研究所。

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