School of Chemical and Biomedical Engineering, Nanyang Technological University, Singapore, Singapore.
School of Chemical and Biomedical Engineering, Nanyang Technological University, Singapore, Singapore.
Comput Biol Med. 2015 May;60:86-91. doi: 10.1016/j.compbiomed.2015.02.011. Epub 2015 Feb 23.
Lymph nodes segmentation is a tedious process with large inter-user variability when performed manually. To facilitate lymph nodes assessment for lung cancer patient, we present an automatic and improved snake segmentation method for thoracic lymph nodes on CT images in this paper. We first investigated the performance of both edge-based and region-based snake algorithms for the segmentation task, using a B-spline contour parameterization. The effect of the number of B-spline control points on the snake performance was also examined. Both edge-based and region-based snakes were found to have their own advantages and disadvantages for lymph nodes segmentation. We further developed a method of region-based snake with edge constraint, which utilizes a self-adjusting mechanism to integrate both edge and region information in a constructive manner. The average Dice Similarity Coefficient obtained was 0.853 ± 0.059 and 0.841 ± 0.108 for the baseline and follow-up lymph nodes respectively using the proposed method. The method was found to be an effective lymph node segmentation method and would potentially be useful to help with treatment response evaluations in the clinical practice.
淋巴结分割是一个繁琐的过程，手动操作时用户之间的差异很大。为了方便对肺癌患者的淋巴结进行评估，我们在本文中提出了一种自动且改进的 CT 图像上胸部淋巴结的 Snake 分割方法。我们首先研究了基于边缘和基于区域的 Snake 算法在 B-样条轮廓参数化条件下的分割任务中的性能，还检查了 B-样条控制点数量对 Snake 性能的影响。基于边缘和基于区域的 Snake 算法都有各自的优缺点，适用于淋巴结分割。我们进一步开发了一种具有边缘约束的基于区域的 Snake 方法，它利用自适应机制以一种建设性的方式整合边缘和区域信息。使用所提出的方法，基线和随访淋巴结的平均 Dice 相似系数分别为 0.853 ± 0.059 和 0.841 ± 0.108。该方法被证明是一种有效的淋巴结分割方法，有望在临床实践中帮助评估治疗反应。
