Sundareswaran Kartik S, Frakes David H, Fogel Mark A, Soerensen Dennis D, Oshinski John N, Yoganathan Ajit P
Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
J Magn Reson Imaging. 2009 Jan;29(1):155-65. doi: 10.1002/jmri.21579.
To develop and validate a multidimensional segmentation and filtering methodology for accurate blood flow velocity field reconstruction from phase-contrast magnetic resonance imaging (PC MRI).
The proposed technique consists of two steps: (1) the boundary of the vessel is automatically segmented using the active contour approach; and (2) the noise embedded within the segmented vector field is selectively removed using a novel fuzzy adaptive vector median filtering (FAVMF) technique. This two-step segmentation process was tested and validated on 111 synthetically generated PC MRI slices and on 10 patients with congenital heart disease.
The active contour technique was effective for segmenting blood vessels having a sensitivity and specificity of 93.1% and 92.1% using manual segmentation as a reference standard. FAVMF was the superior technique in filtering out noise vectors, when compared with other commonly used filters in PC MRI (P < 0.05). The peak wall shear rate calculated from the PC MRI data (248 +/- 39 sec(-1)), was significantly decreased to (146 +/- 26 sec(-1)) after the filtering process.
The proposed two-step segmentation and filtering methodology is more accurate compared to a single-step segmentation process for post-processing of PC MRI data.
开发并验证一种多维分割和滤波方法，用于从相位对比磁共振成像（PC MRI）中准确重建血流速度场。
所提出的技术包括两个步骤：（1）使用活动轮廓法自动分割血管边界；（2）使用一种新型模糊自适应矢量中值滤波（FAVMF）技术选择性去除分割矢量场内嵌入的噪声。在111个合成生成的PC MRI切片和10例先天性心脏病患者身上对这个两步分割过程进行了测试和验证。
以手动分割作为参考标准，活动轮廓技术在分割血管方面有效，灵敏度和特异性分别为93.1%和92.1%。与PC MRI中其他常用滤波器相比，FAVMF在滤除噪声矢量方面是更优的技术（P < 0.05）。从PC MRI数据计算出的峰值壁面剪切率（248 +/- 39秒^(-1)）在滤波过程后显著降低至（146 +/- 26秒^(-1)）。
与PC MRI数据后处理的单步分割过程相比，所提出的两步分割和滤波方法更准确。
