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Motion Correction for Dynamic Contrast-Enhanced CMR Perfusion Images Using a Consecutive Finite Element Model Warping

机译:使用连续有限元模型翘曲对动态增强CMR灌注图像进行运动校正

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摘要

We present results of a non-rigid registration algorithm to correct breathing motion in cardiac MR perfusion sequences applied to the STACOM 2014 Motion Correction Challenge dataset. The algorithm is based on the finite element method whereby a 2D free form deformation model is deformed to match image features. Image warping is performed through global-to-local mapping of motion parameters. To overcome the contrast intensity problem in the perfusion images, the registration was applied consecutively between adjacent frames. Eleven cases were provided by the challenge: Ten cases were ECG-gated MR perfusion images with rest and adenosine-induced stress series, while the last case was an ungated MR perfusion stress acquisition. The algorithm achieved good results in terms of modified Hausdorff distance: 1.31±0.93 pixels (max: 6.5 pixel), horizontal shifting < 4.5 pixels, and vertical shifting: < 4 pixels. Moderate Jaccard index: 0.57 ± 0.14 was achieved.
机译:我们提出了一种非刚性配准算法的结果来纠正应用于STACOM 2014运动校正挑战数据集的心脏MR灌注序列中的呼吸运动。该算法基于有限元方法,从而使2D自由形式变形模型变形以匹配图像特征。图像变形是通过运动参数的全局到局部映射来执行的。为了克服灌注图像中的对比度强度问题,在相邻帧之间连续应用配准。挑战提供了11例:10例是ECG门控MR灌注图像,包括静息和腺苷诱发的压力系列,而最后一例是无门诊MR灌注应力获取。该算法在修改的Hausdorff距离:1.31±0.93像素(最大:6.5像素),水平移位<4.5像素和垂直移位:<4像素方面取得了良好的效果。中等的贾卡德指数:达到0.57±0.14。

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