Vasilic Branimir, Wehrli Felix W
Department of Radiology, the University of Pennsylvania Medical Center, 3400 Spruce Street, 1st Floor Founders, MRI Leaming Center, Philadelphia, PA 19104 USA.
IEEE Trans Med Imaging. 2005 Dec;24(12):1574-85. doi: 10.1109/TMI.2005.859192.
Recent advances in micro-magnetic resonance imaging have shown the possibility of in vivo assessment of trabecular bone architecture. However, the small feature size and relatively low signal-to-noise ratio (SNR) achievable in vivo cause the intensity histogram to be unimodal. The critical first step in the processing of these images is the extraction of bone volume fraction for each voxel. Here, we propose a local threshold algorithm (LTA) that determines the marrow intensity value in the neighborhood of each voxel based on nearest-neighbor statistics. Using the local marrow intensities we threshold the image and scale the intensities of voxels partially occupied by bone to produce a marrow volume fraction map of the trabecular bone region. We show that structural parameters derived with the LTA are highly correlated with those obtained with the previously published histogram deconvolution algorithm (HDA) and that the LTA is robust to image noise corruption. The LTA is found to correctly identify trabeculae with a significantly higher reliability than HDA. Finally, we demonstrate that the LTA is superior in preserving connectivity by showing for 75 in vivo images that the genus of the trabecular bone surface is always higher than when processed with the HDA.
微磁共振成像的最新进展表明了对小梁骨结构进行体内评估的可能性。然而，体内可实现的小特征尺寸和相对较低的信噪比（SNR）导致强度直方图为单峰。处理这些图像的关键第一步是提取每个体素的骨体积分数。在此，我们提出一种局部阈值算法（LTA），该算法基于最近邻统计确定每个体素邻域内的骨髓强度值。利用局部骨髓强度，我们对图像进行阈值处理，并对部分被骨占据的体素强度进行缩放，以生成小梁骨区域的骨髓体积分数图。我们表明，用LTA得出的结构参数与用先前发表的直方图反卷积算法（HDA）获得的参数高度相关，并且LTA对图像噪声干扰具有鲁棒性。发现LTA比HDA能以显著更高的可靠性正确识别小梁。最后，通过对75幅体内图像的展示，即小梁骨表面的亏格总是高于用HDA处理时的情况，我们证明LTA在保持连通性方面更具优势。
