GE Hungary Healthcare Division, Petőfi Sándor sgt. 10, Szeged 6722, Hungary.
Comput Methods Programs Biomed. 2013 Aug;111(2):315-29. doi: 10.1016/j.cmpb.2013.04.017. Epub 2013 May 29.
Computer assisted analysis of organs has an important role in clinical diagnosis and therapy planning. As well as the visualization, the manipulation of 3-dimensional (3D) objects are key features of medical image processing tools. The goal of this work was to develop an efficient and easy to use tool that allows the physician to partition a segmented organ into its segments or lobes. The proposed tool allows the user to define a cutting surface by drawing some traces on 2D sections of a 3D object, cut the object into two pieces with a smooth surface that fits the input traces, and iterate the process until the object is partitioned at the desired level. The tool is based on an algorithm that interpolates the user-defined traces with B-spline surface and computes a binary cutting volume that represents the different sides of the surface. The computation of the cutting volume is based on the multi-resolution triangulation of the B-spline surface. The proposed algorithm was integrated into an open-source medical image processing framework. Using the tool, the user can select the object to be partitioned (e.g. segmented liver), define the cutting surface based on the corresponding medical image (medical image visualizing the internal structure of the liver), cut the selected object, and iterate the process. In case of liver segment separation, the cuts can be performed according to a predefined sequence, which makes it possible to label the temporary as well as the final partitions (lobes, segments) automatically. The presented tool was evaluated for anatomical segment separation of the liver involving 14 cases and virtual liver tumor resection involving one case. The segment separation was repeated 3 different times by one physician for all cases, and the average and the standard deviation of segment volumes were computed. According to the test experiences the presented algorithm proved to be efficient and user-friendly enough to perform free form cuts for liver segment separation and virtual liver tumor resection. The volume quantification of segments showed good correlation with the prior art and the vessel-based liver segment separation, which demonstrate the clinical usability of the presented method.
计算机辅助分析器官在临床诊断和治疗计划中具有重要作用。除了可视化之外，三维（3D）对象的操作也是医学图像处理工具的关键特征。这项工作的目的是开发一种高效且易于使用的工具，使医生能够将分割后的器官分割成其各个段或叶。所提出的工具允许用户通过在 3D 对象的 2D 切片上绘制一些轨迹来定义切割面，用与输入轨迹拟合的光滑表面将对象切割成两部分，并迭代该过程，直到将对象分割到所需的水平。该工具基于一种算法，该算法通过 B 样条曲面内插用户定义的轨迹，并计算表示曲面不同侧的二进制切割体积。切割体积的计算基于 B 样条曲面的多分辨率三角剖分。所提出的算法已集成到开源医学图像处理框架中。使用该工具，用户可以选择要分割的对象（例如分割后的肝脏），根据相应的医学图像（显示肝脏内部结构的医学图像）定义切割面，切割所选对象，并迭代该过程。在肝脏分段分离的情况下，可以根据预定义的序列进行切割，从而可以自动标记临时和最终分区（叶，段）。所提出的工具已针对涉及 14 个病例的肝脏解剖分段分离和一个病例的虚拟肝脏肿瘤切除进行了评估。所有病例均由一位医生重复进行了 3 次分段分离，计算了分段体积的平均值和标准差。根据测试经验，所提出的算法被证明效率高且用户友好，足以进行肝脏分段分离和虚拟肝脏肿瘤切除的自由形式切割。分段的体积量化与先前的技术和基于血管的肝脏分段分离具有很好的相关性，这证明了所提出方法的临床可用性。
