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Segmentation of Myocardial Boundaries in Tagged Cardiac MRI Using Active Contours: A Gradient-Based Approach Integrating Texture Analysis

机译:使用主动轮廓在标记的心脏MRI中分割心肌边界:结合纹理分析的基于梯度的方法

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摘要

The noninvasive assessment of cardiac function is of first importance for the diagnosis of cardiovascular diseases. Among all medical scanners only a few enables radiologists to evaluate the local cardiac motion. Tagged cardiac MRI is one of them. This protocol generates on Short-Axis (SA) sequences a dark grid which is deformed in accordance with the cardiac motion. Tracking the grid allows specialists a local estimation of cardiac geometrical parameters within myocardium. The work described in this paper aims to automate the myocardial contours detection in order to optimize the detection and the tracking of the grid of tags within myocardium. The method we have developed for endocardial and epicardial contours detection is based on the use of texture analysis and active contours models. Texture analysis allows us to define energy maps more efficient than those usually used in active contours methods where attractor is often based on gradient and which were useless in our case of study, for quality of tagged cardiac MRI is very poor.
机译:心功能的非侵入性评估对于心血管疾病的诊断至关重要。在所有医疗扫描仪中,只有少数使放射科医生能够评估局部心脏运动。标记心脏核磁共振成像就是其中之一。该协议在短轴(SA)序列上生成一个暗网格,该暗网格根据心脏运动而变形。跟踪网格可以使专家局部估计心肌内的心脏几何参数。本文所述的工作旨在使心肌轮廓检测自动化,以优化心肌内标记网格的检测和跟踪。我们开发的用于心内膜和心外膜轮廓检测的方法基于纹理分析和活动轮廓模型的使用。纹理分析使我们能够定义能量图,而能量图通常比主动轮廓法通常使用的能量图有效,在这些方法中,吸引子通常基于梯度,并且在我们的研究案例中没有用,因为标记心脏MRI的质量非常差。

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