南方医科大学学报 ›› 2015, Vol. 35 ›› Issue (11): 1579-.

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基于高维全变分正则化的鲁棒低剂量CT心肌灌注去卷积方法

龚长飞,曾栋,边兆英,张华,张璋,张敬,黄静,马建华   

  • 出版日期:2015-11-20 发布日期:2015-11-20

Robust low-dose CT myocardial perfusion deconvolution via high-dimension total
variation regularization

  • Online:2015-11-20 Published:2015-11-20

摘要: 目的研发一种基于高维全变分(high dimension total variation, HDTV)先验的CT 心肌灌注(computed tomography
myocardial perfusion, CT-MP)去卷积方法。方法首先对低剂量CT-MP数据进行灌注去卷积建模,其后通过引入HDTV正则化
修正模型最小化解的一致性。其中,HDTV利用心肌血管空间结构相似性和心肌血流信号时间连续性。结果XCAT心肌灌注
仿真数据和猪心肌灌注数据实验表明,同已有的方法相比,本方法能更有效地抑制低剂量血流动力学参数图中的噪声和伪影,
同时较好地保持具有诊断意义的结构信息。结论本文方法可实现低剂量CT-MPI血流动力学参数图的优质成像。

Abstract: Objective To develop a computed tomography myocardial perfusion (CT-MP) deconvolution algorithm by
incorporating high-dimension total variation (HDTV) regularization. Methods A perfusion deconvolution model was
formulated for the low-dose CT-MPI data, followed by HDTV regularization to regularize the consistency of the solution by
fusing the spatial correlation of the vascular structure and the temporal continuation of the blood flow signal. Results Both
qualitative and quantitative studies were conducted using XCAT and pig myocardial perfusion data to evaluate the present
algorithm. The experimental results showed that this algorithm achieved hemodynamic parameter maps with better
performances than the existing methods in terms of streak-artifacts suppression, noise-resolution tradeoff, and diagnosis
structure preservation. Conclusion The proposed algorithm can achieve high-quality hemodynamic parameter maps in
low-dose CT-MPI.