Department of Biomedical Engineering, Cardiovascular Research Institute Maastricht, Maastricht University, 6200MD Maastricht, The Netherlands.
IEEE Trans Med Imaging. 2010 May;29(5):1114-23. doi: 10.1109/TMI.2009.2037955. Epub 2010 Mar 22.
The new SinMod method extracts motion from magnetic resonance imaging (MRI)-tagged (MRIT) image sequences. Image intensity in the environment of each pixel is modeled as a moving sine wavefront. Displacement is estimated at subpixel accuracy. Performance is compared with the harmonic-phase analysis (HARP) method, which is currently the most common method used to detect motion in MRIT images. SinMod can handle line tags, as well as speckle patterns. In artificial images (tag distance six pixels), SinMod detects displacements accurately (error < 0.02 pixels). Effects of noise are suppressed effectively. Sharp transitions in motion at the boundary of an object are smeared out over a width of 0.6 tag distance. For MRIT images of the heart, SinMod appears less sensitive to artifacts, especially later in the cardiac cycle when image quality deteriorates. For each pixel, the quality of the sine-wave model in describing local image intensity is quantified objectively. If local quality is low, artifacts are avoided by averaging motion over a larger environment. Summarizing, SinMod is just as fast as HARP, but it performs better with respect to accuracy of displacement detection, noise reduction, and avoidance of artifacts.
新的 SinMod 方法从磁共振成像 (MRI) 标记 (MRIT) 图像序列中提取运动。每个像素环境中的图像强度被建模为移动的正弦波前。位移以亚像素精度估计。性能与当前用于检测 MRIT 图像中运动的最常用方法——谐波相位分析 (HARP) 方法进行了比较。SinMod 可以处理线标记以及散斑图案。在人工图像（标记距离为 6 像素）中，SinMod 可以准确检测到位移（误差 < 0.02 像素）。噪声的影响得到有效抑制。在物体边界处运动的急剧过渡在 0.6 个标记距离的宽度上被模糊。对于心脏的 MRIT 图像，SinMod 对伪影的敏感性似乎较低，尤其是在心脏周期的后期，图像质量恶化时。对于每个像素，用正弦波模型描述局部图像强度的质量可以客观地量化。如果局部质量较低，则可以通过在更大的环境中平均运动来避免伪影。总之，SinMod 与 HARP 一样快，但在位移检测精度、降噪和避免伪影方面表现更好。
