Fischl Bruce, Salat David H, van der Kouwe André J W, Makris Nikos, Ségonne Florent, Quinn Brian T, Dale Anders M
Department of Radiology, MGH, Athinoula A Martinos Center, Harvard Medical School, Charlestown, MA 02129, USA.
Neuroimage. 2004;23 Suppl 1:S69-84. doi: 10.1016/j.neuroimage.2004.07.016.
We present a set of techniques for embedding the physics of the imaging process that generates a class of magnetic resonance images (MRIs) into a segmentation or registration algorithm. This results in substantial invariance to acquisition parameters, as the effect of these parameters on the contrast properties of various brain structures is explicitly modeled in the segmentation. In addition, the integration of image acquisition with tissue classification allows the derivation of sequences that are optimal for segmentation purposes. Another benefit of these procedures is the generation of probabilistic models of the intrinsic tissue parameters that cause MR contrast (e.g., T1, proton density, T2*), allowing access to these physiologically relevant parameters that may change with disease or demographic, resulting in nonmorphometric alterations in MR images that are otherwise difficult to detect. Finally, we also present a high band width multiecho FLASH pulse sequence that results in high signal-to-noise ratio with minimal image distortion due to B0 effects. This sequence has the added benefit of allowing the explicit estimation of T2* and of reducing test-retest intensity variability.
我们提出了一套技术，用于将生成一类磁共振图像（MRI）的成像过程的物理原理嵌入到分割或配准算法中。这使得算法对采集参数具有显著的不变性，因为在分割过程中明确地对这些参数对各种脑结构对比度特性的影响进行了建模。此外，将图像采集与组织分类相结合，可以导出最适合分割目的的序列。这些方法的另一个好处是生成了导致磁共振对比度的内在组织参数（例如，T1、质子密度、T2*）的概率模型，从而能够获取这些可能随疾病或人口统计学因素而变化的生理相关参数，这些参数会导致磁共振图像中出现难以检测到的非形态学改变。最后，我们还展示了一种高带宽多回波FLASH脉冲序列，该序列在由于B0效应导致的图像失真最小的情况下能产生高信噪比。这个序列还有一个额外的好处，即允许明确估计T2*并减少重测强度变异性。
