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A Comparative Study on Interpolation Methods in Rebinning Circular Fan-Beam Data into Parallel-Beam Data

机译:将圆形扇形束数据合并为平行束数据的插值方法的比较研究

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Computed Tomography (CT) scanners evolved from simple parallel-beam geometry into more complex fan-beam geometry. The rebinning mechanism to convert fan-beam projections to parallel-beam projections is one of the methods simplifying the reconstruction of the CT image. Various interpolation methods result in different numerical presentations and noisy textures in the reconstructed CT images. This paper evaluates three interpolation methods, linear, frequency domain and higher order in rebinning fan-beam data into parallel-beam data in the framework of the FBP algorithm in parallel-beam CTs. The high-contrast spatial resolution, modulation transfer function (MTF), and noise are used to quantify the image quality. The noise is expressed as the noise power spectrum (NPS) and noise variance of the reconstructed image containing only Poisson distributed noise. Our results show that the higher order interpolation, cubic-spline, is the most helpful to improve the image quality in rebinning. We further demonstrate that the rebinning data gives more satisfactory results for assessment of noise variance in comparison with the fan-beam data.
机译:计算机断层扫描(CT)扫描仪已从简单的平行光束几何结构演变为更复杂的扇形光束几何结构。将扇形束投影转换为平行束投影的重组机制是简化CT图像重建的方法之一。各种插值方法会在重建的CT图像中产生不同的数值表示和嘈杂的纹理。本文在并行束CT的FBP算法框架下,评估了将扇形束数据重新组合为并行束数据时使用的线性,频域和高阶三种插值方法。高对比度的空间分辨率,调制传递函数(MTF)和噪声用于量化图像质量。噪声表示为仅包含泊松分布噪声的重建图像的噪声功率谱(NPS)和噪声方差。我们的结果表明,高阶插值三次样条对改善合并图像的质量最有帮助。我们进一步证明,与扇形束数据相比,重组数据为噪声方差评估提供了更令人满意的结果。

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