Bergeest Jan-Philip, Rohr Karl
University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg, Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group.
Med Image Comput Comput Assist Interv. 2011;14(Pt 1):645-52. doi: 10.1007/978-3-642-23623-5_81.
Accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression in high-throughput screening applications. We propose a new approach for segmenting cell nuclei which is based on active contours and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images of different cell types. We have also performed a quantitative comparison with previous segmentation approaches.
在高通量筛选应用中，荧光显微镜图像中细胞的准确高效分割对于蛋白质表达定量至关重要。我们提出了一种基于活动轮廓和凸能量泛函的细胞核分割新方法。与之前的工作相比，我们的方法能确定全局解。因此，该方法不会受局部极小值影响，分割结果也不依赖于初始化。我们还提出了一种有效计算该解的数值方法。我们使用不同细胞类型的荧光显微镜图像评估了我们方法的性能。我们还与之前的分割方法进行了定量比较。
