Baumann T, Langer M
Abteilung Röntgendiagnostik, Universitätsklinikum Freiburg, Hugstetter Str. 55, 79106, Freiburg, Deutschland,
Radiologe. 2013 Sep;53(9):805-9. doi: 10.1007/s00117-013-2513-6.
Image post-processing of large thin-slice radiological datasets relies on increasingly diverse and complex algorithms. Basic techniques of visualization, segmentation and data analysis will be presented in this article focusing on methods which are integrated into the majority of current viewing and reporting tools, such as multiplanar reformation, volume rendering or basic segmentation. Subsequently, more complex methods and a possible role of post-processing algorithms in the radiology of the future will be discussed.
大型薄层放射学数据集的图像后处理依赖于越来越多样和复杂的算法。本文将介绍可视化、分割和数据分析的基本技术,重点关注那些集成到大多数当前查看和报告工具中的方法,如多平面重组、容积再现或基本分割。随后,将讨论更复杂的方法以及后处理算法在未来放射学中的可能作用。