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Enhancement of venous vasculature in susceptibility weighted images of the brain using multi-scale vessel enhancement filtering

机译:使用多尺度血管增强滤波增强脑部敏感性加权图像中的静脉血管

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To enhance the visibility of veins of the brain in susceptibility weighted imaging (SWI)-based MR venography using a 3D multi-scale vessel enhancement filter. The magnitude data of SWI were convolved with the second-order derivatives of the Gaussian function. Eigenvalue analysis of the Hessian matrix of the convolved magnitude images was used to enhance the veins. Multi-scale integration was formulated by the combination of maximum value among the normalized filter responses at multiple scales. The resultant 3D multi-scale MR venography demonstrated substantially enhanced visibility of the veins in SWI of the brain. Unlike the conventional SWI, the proposed technique does not suffer from the off-resonance artifact in the brain regions with severe field inhomogeneity and the signal loss in peripheral region of the brain in minimum-intensity projection. Both the background tissue in the brain and the noise in air were well suppressed in the filtered MR venography. Three-dimensional multi-scale vessel enhancement filtering based on the eigenvalue analysis of the Hessian matrix can effectively enhance the visibility of veins in susceptibility weighted images of the brain.
机译:为了在使用3D多尺度血管增强滤镜的基于磁化率加权成像(SWI)的MR静脉造影中增强脑静脉的可见性。 SWI的幅度数据与高斯函数的二阶导数进行卷积。卷积大小图像的Hessian矩阵的特征值分析用于增强静脉。多尺度积分是通过将多个尺度的归一化滤波器响应之间的最大值相结合来制定的。最终的3D多尺度MR静脉造影显示出大脑SWI中静脉的可见度大大提高。与传统的SWI不同,所提出的技术不会在严重强度不均匀的大脑区域出现偏共振伪影,并且在最小强度投影中不会出现大脑周围区域的信号丢失。在过滤后的MR静脉造影中,大脑的背景组织和空气中的噪音都得到了很好的抑制。基于Hessian矩阵特征值分析的三维多尺度血管增强滤波可以有效增强大脑易感性加权图像中静脉的可见度。

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