基于飞行焦点CT数据的压缩感知图像重建研究。
An Investigation of Compressive-sensing Image Reconstruction from Flying-focal-spot CT Data.
作者信息
Xia D, Bian J, Han X, Sidky E Y, Pan X
机构信息
Department of Radiology, The University of Chicago 5841 S Maryland Avenue, Chicago, IL 60637.
出版信息
IEEE Nucl Sci Symp Conf Rec (1997). 2009 Jan 1;2009:3458-3462. doi: 10.1109/NSSMIC.2009.5401787.
Flying-focal-spot (FFS) technique has been used for improving the sampling condition in advanced clinical CT by collecting multiple cone-beam data sets with the focal-spot at different locations at each "projection view". It has been demonstrated that the increased sampling rate in FFS scans can substantially reduce aliasing artifacts in reconstructed images. However, the increase of the sampling density through multiple illuminations at each view can result in the increase of radiation dose to the imaged subject. In this work, we have applied a compressive-sensing (CS)-based algorithm to image reconstruction from data acquired in FFS scans. The results of the study demonstrate that aliasing artifacts observed images reconstructed by use of analytic algorithms can be suppressed effectively in images reconstructed with this CS-based algorithm from only data acquired at one FFS scan.
飞焦点（FFS）技术已被用于通过在每个“投影视图”中使用位于不同位置的焦点收集多个锥束数据集来改善先进临床CT中的采样条件。已经证明，FFS扫描中增加的采样率可以显著减少重建图像中的混叠伪影。然而，通过在每个视图中多次照射来增加采样密度会导致对成像对象的辐射剂量增加。在这项工作中，我们将基于压缩感知（CS）的算法应用于从FFS扫描获取的数据进行图像重建。研究结果表明，使用解析算法重建的图像中观察到的混叠伪影可以在仅从一次FFS扫描获取的数据使用这种基于CS的算法重建的图像中得到有效抑制。
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