在相衬视频显微镜中利用最大流/最小割算法，运用时间信息进行细胞分割。
Employing temporal information for cell segmentation using max-flow/min-cut in phase-contrast video microscopy.
作者信息
Massoudi Amir, Sowmya Arcot, Mele Katarina, Semenovich Dimitri
机构信息
Department of Computer Science and Engineering, University of New South Wales, Sydney, New South Wales 2052, Australia.
出版信息
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:5985-8. doi: 10.1109/IEMBS.2011.6091479.
Cell segmentation is a crucial step in many bio-medical image analysis applications and it can be considered as an important part of a tracking system. Segmentation in phase-contrast images is a challenging task since in this imaging technique, the background intensity is approximately similar to the cell pixel intensity. In this paper we propose an interactive automatic pixel level segmentation algorithm, that uses temporal information to improve the segmentation result. This algorithm is based on the max-flow/min-cut algorithm and can be solved in polynomial time. This method is not restricted to any specific cell shape and segments cells of various shapes and sizes. The results of the proposed algorithm show that using the temporal information does improve segmentation considerably.
细胞分割是许多生物医学图像分析应用中的关键步骤，并且可以被视为跟踪系统的重要组成部分。相衬图像中的分割是一项具有挑战性的任务，因为在这种成像技术中，背景强度与细胞像素强度大致相似。在本文中，我们提出了一种交互式自动像素级分割算法，该算法利用时间信息来改善分割结果。该算法基于最大流/最小割算法，并且可以在多项式时间内求解。此方法不限于任何特定的细胞形状，能够分割各种形状和大小的细胞。所提算法的结果表明，使用时间信息确实能显著改善分割效果。
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