Department of Radiology, The University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637, USA.
Med Phys. 2010 May;37(5):2159-66. doi: 10.1118/1.3395579.
Computerized liver extraction from hepatic CT images is challenging because the liver often abuts other organs of a similar density. The purpose of this study was to develop a computer-aided measurement of liver volumes in hepatic CT.
The authors developed a computerized liver extraction scheme based on geodesic active contour segmentation coupled with level-set contour evolution. First, an anisotropic diffusion filter was applied to portal-venous-phase CT images for noise reduction while preserving the liver structure, followed by a scale-specific gradient magnitude filter to enhance the liver boundaries. Then, a nonlinear grayscale converter enhanced the contrast of the liver parenchyma. By using the liver-parenchyma-enhanced image as a speed function, a fast-marching level-set algorithm generated an initial contour that roughly estimated the liver shape. A geodesic active contour segmentation algorithm coupled with level-set contour evolution refined the initial contour to define the liver boundaries more precisely. The liver volume was then calculated using these refined boundaries. Hepatic CT scans of 15 prospective liver donors were obtained under a liver transplant protocol with a multidetector CT system. The liver volumes extracted by the computerized scheme were compared to those traced manually by a radiologist, used as "gold standard."
The mean liver volume obtained with our scheme was 1504 cc, whereas the mean gold standard manual volume was 1457 cc, resulting in a mean absolute difference of 105 cc (7.2%). The computer-estimated liver volumetrics agreed excellently with the gold-standard manual volumetrics (intraclass correlation coefficient was 0.95) with no statistically significant difference (F = 0.77; p(F < or = f) = 0.32). The average accuracy, sensitivity, specificity, and percent volume error were 98.4%, 91.1%, 99.1%, and 7.2%, respectively. Computerized CT liver volumetry would require substantially less completion time (compared to an average of 39 min per case by manual segmentation).
The computerized liver extraction scheme provides an efficient and accurate way of measuring liver volumes in CT.
从肝脏 CT 图像中提取肝脏是具有挑战性的，因为肝脏通常与其他密度相似的器官相邻。本研究的目的是开发一种基于测地线主动轮廓分割和水平集轮廓演化的计算机辅助肝脏体积测量方法。
作者开发了一种基于测地线主动轮廓分割和水平集轮廓演化的计算机肝脏提取方案。首先，对门静脉期 CT 图像应用各向异性扩散滤波器进行降噪，同时保留肝脏结构，然后应用特定尺度的梯度幅度滤波器增强肝脏边界。然后，使用非线性灰度转换器增强肝脏实质的对比度。通过使用增强后的肝实质图像作为速度函数，快速行进水平集算法生成一个大致估计肝脏形状的初始轮廓。然后使用测地线主动轮廓分割算法和水平集轮廓演化对初始轮廓进行细化，以更精确地定义肝脏边界。最后，使用这些细化后的边界计算肝脏体积。根据肝移植方案，使用多排 CT 系统对 15 例前瞻性肝供体进行肝 CT 扫描。将计算机方案提取的肝脏体积与放射科医生手动勾画的“金标准”进行比较。
我们的方案获得的平均肝脏体积为 1504cc，而金标准手动体积的平均为 1457cc，平均绝对差值为 105cc（7.2%）。计算机估计的肝脏体积与金标准手动体积非常吻合（组内相关系数为 0.95），差异无统计学意义（F=0.77；p(F<=f)=0.32）。计算机 CT 肝脏体积测量的平均准确性、敏感性、特异性和体积误差百分比分别为 98.4%、91.1%、99.1%和 7.2%。与手动分割相比，计算机 CT 肝脏体积测量所需的时间大大减少（平均每个病例需要 39 分钟）。
计算机肝脏提取方案为 CT 中肝脏体积的测量提供了一种高效、准确的方法。
