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Digital breast tomosynthesis reconstruction with an adaptive voxel grid

机译:自适应体素网格数字化胸部断层合成

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In digital breast tomosynthesis (DBT) volume datasets are typically reconstructed with an anisotropic voxel size, where the in-plane voxel size usually reflects the detector pixel size (e.g., 0.1 mm), and the slice separation is generally between 0.5-1.0 mm. Increasing the tomographic angle is expected to give better 3D image quality; however, the slice spacing in the reconstruction should be reduced, otherwise one may risk losing fine-scale image detail (e.g., small microcalcifications). An alternative strategy consists of reconstructing on an adaptive voxel grid, where the voxel height at each location is adapted based on the backprojected data at this location, with the goal to improve image quality for microcalcifications. In this paper we present an approach for generating such an adaptive voxel grid. This approach is based on an initial reconstruction step that is performed at a finer slice-spacing combined with a selection of an "optimal" height for each voxel. This initial step is followed by a (potentially iterative) reconstruction acting now on the adaptive grid only.
机译:在数字乳房断层合成(DBT)中,通常使用各向异性体素大小重建体积数据集,其中面内体素大小通常反映检测器像素大小(例如0.1毫米),并且切片间距通常在0.5-1.0毫米之间。预期增加层析成像角度可提供更好的3D图像质量;但是,应减少重建中的切片间距,否则可能会有丢失精细图像细节的风险(例如微小的微钙化)。一种替代策略包括在自适应体素网格上进行重建,其中根据该位置的反投影数据来调整每个位置的体素高度,以提高微钙化的图像质量。在本文中,我们提出了一种生成这种自适应体素网格的方法。该方法基于初始重建步骤,该步骤在更精细的切片间距下执行,并结合了每个体素的“最佳”高度选择。在此初始步骤之后是(可能迭代的)重构,此重构现在仅作用于自适应网格。

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