利用可变形网格模型从MRI序列中检测心脏异常

Felipe M. Parages, J. Brankov
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引用次数: 0

摘要

在这项工作中,我们探索了估计心室运动的潜力,使用可变形网格模型(DMM),在MRI心脏门控图像序列中检测心脏病理,如高血压和二尖瓣反流。在DMM中,左心室运动是通过沿着组合标记和电影MRI序列的像素强度变化变形3d网格来估计的。其次,利用DMM获得的密集运动场,利用b样条模型计算LV的三维扭转映射。从扭转图中提取的特征通过Fisher判别分析用于检测高血压和二尖瓣反流。最后,将DMM运动检测性能与其他已知的运动跟踪方法(如基于特征(FB)分析和未包裹相位应变(SUP))进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of cardiac abnormalities from MRI sequences by using a deformable mesh model
In this work, we explore the potential of estimated ventricle motion, using a deformable mesh model (DMM), to detect cardiac pathologies such as hypertension and mitral regurgitation in MRI cardiac gated image sequences. In DMM, left ventricle motion was estimated by deforming a 3D-mesh along pixel-intensity variations of combined tagged and cine MRI sequences. Next, dense motion fields obtained from DMM were used to compute 3D torsion maps for the LV using a B-Spline model. Features extracted from the torsion maps were used for detection of hypertension and mitral regurgitation by performing Fisher Discriminant Analysis. Finally, detection performance of DMM motion was compared to other known motion-tracking approaches, such as Feature Based (FB) analysis and Unwrapped Phase Strain (SUP).
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