Chen Ying-Cheng, Chen Yung-Chang, Chiang Ann-Shyn, Hsieh Kai-Sheng
Department of Electrical Engineering, National Tsing Hua University, Hsinchu 300, Taiwan, ROC.
Comput Methods Programs Biomed. 2007 May;86(2):141-52. doi: 10.1016/j.cmpb.2007.01.011. Epub 2007 Mar 21.
For common biomedical imaging facilities, such as CT, MRI, and confocal microscopy, the acquired scans are sequential parallel sections. The object of interest in each section image can be extracted by segmentation procedure to form serial parallel planar contours. How to reconstruct a trustworthy surface from these contours is a crucial issue in biomedical 3D visualization. In this paper, we propose an automatic, fast, and reliable surface reconstruction system. An improved correspondence-determining algorithm is proposed in the system to provide more reasonable contour-correspondences than the existing algorithms. It can handle more general input data, and does not produce wrong reconstruction results. A hybrid tiling algorithm is presented to tile the corresponding contours without the requirement of a contour-matching procedure. It can also handle the branching problem without any modification. For degenerate cases and branches, intermediate contours are introduced by means of contour interpolation to enhance the reconstruction results. The surface area and volume are also calculated to facilitate the practical applications.
对于常见的生物医学成像设备,如CT、MRI和共聚焦显微镜,获取的扫描图像是连续的平行切片。通过分割程序可以提取每个切片图像中的感兴趣对象,以形成连续的平行平面轮廓。如何从这些轮廓重建一个可靠的表面是生物医学三维可视化中的一个关键问题。在本文中,我们提出了一种自动、快速且可靠的表面重建系统。该系统中提出了一种改进的对应关系确定算法,以提供比现有算法更合理的轮廓对应关系。它可以处理更一般的输入数据,并且不会产生错误的重建结果。提出了一种混合平铺算法,用于平铺相应的轮廓,而无需轮廓匹配过程。它也可以无需任何修改地处理分支问题。对于退化情况和分支,通过轮廓插值引入中间轮廓以增强重建结果。还计算了表面积和体积以方便实际应用。