Ou J J, Ong R E, Yankeelov T E, Miga M I
Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA.
Phys Med Biol. 2008 Jan 7;53(1):147-63. doi: 10.1088/0031-9155/53/1/010. Epub 2007 Dec 19.
This paper reports on the development and preliminary testing of a three-dimensional implementation of an inverse problem technique for extracting soft-tissue elasticity information via non-rigid model-based image registration. The modality-independent elastography (MIE) algorithm adjusts the elastic properties of a biomechanical model to achieve maximal similarity between images acquired under different states of static loading. A series of simulation experiments with clinical image sets of human breasts were performed to test the ability of the method to identify and characterize a radiographically occult stiff lesion. Because boundary conditions are a critical input to the algorithm, a comparison of three methods for semi-automated surface point correspondence was conducted in the context of systematic and randomized noise processes. The results illustrate that 3D MIE was able to successfully reconstruct elasticity images using data obtained from both magnetic resonance and x-ray computed tomography systems. The lesion was localized correctly in all cases and its relative elasticity found to be reasonably close to the true values (3.5% with the use of spatial priors and 11.6% without). In addition, the inaccuracies of surface registration performed with thin-plate spline interpolation did not exceed empiric thresholds of unacceptable boundary condition error.
本文报道了一种通过基于非刚性模型的图像配准提取软组织弹性信息的逆问题技术的三维实现方法及其初步测试。多模态弹性成像(MIE)算法调整生物力学模型的弹性属性,以在不同静态加载状态下采集的图像之间实现最大程度的相似性。利用一系列人体乳房临床图像集进行了模拟实验,以测试该方法识别和表征影像学隐匿性硬病变的能力。由于边界条件是该算法的关键输入,因此在系统噪声和随机噪声过程的背景下,对三种半自动表面点对应方法进行了比较。结果表明,三维MIE能够使用从磁共振和X射线计算机断层扫描系统获得的数据成功重建弹性图像。在所有病例中病变均被正确定位,其相对弹性与真实值相当接近(使用空间先验时为3.5%,不使用时为11.6%)。此外,使用薄板样条插值进行表面配准的误差未超过不可接受边界条件误差的经验阈值。