Rodríguez Roberto
Digital Signal Processing Group, Institute of Cybernetics, Mathematics and Physics (ICIMAF), Calle 15 no. 551 e/CyD, CP 10 400 Ciudad de la Habana, Cuba.
Comput Methods Programs Biomed. 2006 Apr;82(1):1-9. doi: 10.1016/j.cmpb.2005.10.008. Epub 2006 Mar 23.
This paper presents a strategy for segmenting blood vessels based on the threshold, which combines statistics and scale space filter. By incorporating statistical information, the strategy is capable of reducing over-segmentation. We propose a two-stage strategy which involves: (1) optimal selection of window size and (2) optimal selection of scale. We compared our strategy to two commonly used thresholding techniques. Experimental results showed that our method is much more robust and accurate. Our strategy suggested a modification to Otsu's method. In this application the important information to be extracted from images is only the number of blood vessels present in the images. The proposed segmentation technique is tested on manual segmentation, where segmentation errors less than 3% were observed. The work presented in this paper is a part of a global image analysis process. Therefore, these images will be subject to a further morphometrical analysis in order to diagnose and predict automatically malign tumors.
本文提出了一种基于阈值的血管分割策略，该策略结合了统计信息和尺度空间滤波器。通过纳入统计信息，该策略能够减少过分割。我们提出了一种两阶段策略，包括：(1) 窗口大小的最优选择和 (2) 尺度的最优选择。我们将我们的策略与两种常用的阈值处理技术进行了比较。实验结果表明，我们的方法更加稳健和准确。我们的策略建议对大津法进行改进。在本应用中，要从图像中提取的重要信息仅是图像中存在的血管数量。所提出的分割技术在手动分割上进行了测试，观察到分割误差小于3%。本文所呈现的工作是全局图像分析过程的一部分。因此，这些图像将接受进一步的形态计量分析，以便自动诊断和预测恶性肿瘤。
