Cheng Jierong, Rajapakse Jagath C
School of Computer Engineering, Nanyang Technological University, Singapore 638798, Singapore.
IEEE Trans Biomed Eng. 2009 Mar;56(3):741-8. doi: 10.1109/TBME.2008.2008635. Epub 2008 Nov 11.
We present a method to separate clustered nuclei from fluorescence microscopy cellular images, using shape markers and marking function in a watershed-like algorithm. Shape markers are extracted using an adaptive H-minima transform. A marking function based on the outer distance transform is introduced to accurately separate clustered nuclei. With synthetic images, we quantitatively demonstrate the performance of our method and provide comparisons with existing approaches. On mouse neuronal and Drosophila cellular images, we achieved 6%-7% improvement of segmentation accuracies over earlier methods.
我们提出了一种在分水岭式算法中使用形状标记和标记函数从荧光显微镜细胞图像中分离聚集细胞核的方法。使用自适应H极小值变换提取形状标记。引入基于外部距离变换的标记函数以准确分离聚集的细胞核。通过合成图像,我们定量地展示了我们方法的性能,并与现有方法进行了比较。在小鼠神经元和果蝇细胞图像上,我们相对于早期方法实现了6%-7%的分割精度提升。