Fernandez-de-Manuel Laura, Rubio Jose L, Ledesma-Carbayo Maria J, Pascau Javier, Tellado Jose M, Ramon Enrique, Desco Manuel, Santos Andres
Group of Biomedical Image Technologies, ETSIT, Universidad Politécnica de Madrid, Madrid 28040, Spain.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:3625-8. doi: 10.1109/IEMBS.2009.5333760.
In this work we propose an active surface method to segment complete liver volumes from preoperative CT abdominal images. The method finds the surface that minimizes an energy function combining intensity inside and outside the surface, gradient information and curvature restrictions. The implementation is based on a level set technique following a multi-resolution strategy to reduce computing time. It requires only a single seed point inside the liver to initialize the active surface. The algorithm has been validated on a set of previously diagnosed livers. Resulting segmentations have been supervised by clinicians and radiologists, and numerically evaluated in terms of volume measurements with respect to those obtained from radiologists' manual segmentations. Additionally, radiologists analyzed the necessity of additional corrections on segmenting volumes.
在这项工作中，我们提出了一种主动表面方法，用于从术前腹部CT图像中分割出完整的肝脏体积。该方法找到一个表面，该表面能使结合表面内外强度、梯度信息和曲率限制的能量函数最小化。实现过程基于一种水平集技术，并采用多分辨率策略以减少计算时间。它只需要肝脏内部的一个种子点来初始化主动表面。该算法已在一组先前诊断的肝脏上得到验证。所得的分割结果由临床医生和放射科医生进行监督，并根据与放射科医生手动分割获得的体积测量值进行数值评估。此外，放射科医生分析了在分割体积时进行额外校正的必要性。
