Morigi S, Sgallari F
Department of Mathematics, University of Bologna, P.zza di Porta San Donato 5, 40127 Bologna, Italy.
Comput Med Imaging Graph. 2004 Oct;28(7):377-90. doi: 10.1016/j.compmedimag.2004.07.002.
In medical imaging a three-dimensional (3D) object must often be reconstructed from serial cross-sections to aid in the comprehension of the object's structure as well as to facilitate its automatic manipulation and analysis. The most popular interpolation scheme for a sequence of image slices is the shape-based method, where object information extracted from a given 3D volume image is used in guiding the interpolation process. The paper presents a level set reformulation of the well-known shape-based method as well as a new automatic level set method, which offers better performance. In particular, we focus on X-ray examinations of long bones, which also requires us to deal with the problem of an optimal slice positioning. To this aim, a 2D version of the proposed algorithm will be used to localize a subset of slices from the entire volume image. A number of experiments were performed on computed tomographic real images to evaluate the proposed approach. The experimental results show a substantial improvement of visual effects (qualitative evaluation) using the proposed method in comparison to both the conventional gray-level interpolation scheme and the shape-based method. Compared with the shape-based interpolation scheme the proposed method has much lower computational cost.
在医学成像中，经常需要从一系列横截面重建三维（3D）物体，以帮助理解物体的结构，并便于对其进行自动操作和分析。对于一系列图像切片，最流行的插值方案是基于形状的方法，其中从给定的3D体积图像中提取的物体信息用于指导插值过程。本文提出了一种对著名的基于形状的方法的水平集重新表述，以及一种性能更好的新的自动水平集方法。特别是，我们专注于长骨的X射线检查，这也要求我们处理最佳切片定位的问题。为此，将使用所提出算法的二维版本从整个体积图像中定位切片子集。在计算机断层扫描真实图像上进行了大量实验，以评估所提出的方法。实验结果表明，与传统的灰度插值方案和基于形状的方法相比，使用所提出的方法在视觉效果（定性评估）上有显著改善。与基于形状的插值方案相比，所提出的方法具有更低的计算成本。
