Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BioQuant, IPMB, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 267, 69120 Heidelberg, Germany.
Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BioQuant, IPMB, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 267, 69120 Heidelberg, Germany.
Med Image Anal. 2015 Jan;19(1):1-14. doi: 10.1016/j.media.2014.07.006. Epub 2014 Aug 11.
The analysis of the motion of subcellular particles in live cell microscopy images is essential for understanding biological processes within cells. For accurate quantification of the particle motion, compensation of the motion and deformation of the cell nucleus is required. We introduce a non-rigid multi-frame registration approach for live cell fluorescence microscopy image data. Compared to existing approaches using pairwise registration, our approach exploits information from multiple consecutive images simultaneously to improve the registration accuracy. We present three intensity-based variants of the multi-frame registration approach and we investigate two different temporal weighting schemes. The approach has been successfully applied to synthetic and live cell microscopy image sequences, and an experimental comparison with non-rigid pairwise registration has been carried out.
对活细胞显微镜图像中亚细胞粒子的运动进行分析对于理解细胞内的生物过程至关重要。为了准确量化粒子的运动，需要对细胞核的运动和变形进行补偿。我们引入了一种用于活细胞荧光显微镜图像数据的非刚性多帧配准方法。与使用两两配准的现有方法相比，我们的方法同时利用多个连续图像的信息来提高配准精度。我们提出了三种基于强度的多帧配准方法变体，并研究了两种不同的时间加权方案。该方法已成功应用于合成和活细胞显微镜图像序列，并与非刚性两两配准进行了实验比较。
