von Wegner Frederic, Ober Tobias, Weber Cornelia, Schürmann Sebastian, Winter René, Friedrich Oliver, Fink Rainer H A, Vogel Martin
University of Heidelberg, Institute of Physiology and Pathophysiology, Medical Biophysics Group, Im Neuenheimer Feld 326, 69120 Heidelberg, Germany.
J Biomed Opt. 2008 Sep-Oct;13(5):054018. doi: 10.1117/1.2982525.
We present an approach for the computation of single-object velocity statistics in a noisy fluorescence image series. The algorithm is applied to molecular imaging data from an in vitro actin-myosin motility assay. We compare the relative efficiency of wavelet and curvelet transform denoising in terms of noise reduction and object restoration. It is shown that while both algorithms reduce background noise efficiently, curvelet denoising restores the curved edges of actin filaments more reliably. Noncrossing spatiotemporal actin trajectories are unambiguously identified using a novel segmentation scheme that locally combines the information of 2-D and 3-D segmentation. Finally, the optical flow vector field for the image sequence is computed via the 3-D structure tensor and mapped to the segmented trajectories. Using single-trajectory statistics, the global velocity distribution extracted from an image sequence is decomposed into the contributions of individual trajectories. The technique is further used to analyze the distribution of the x and y components of the velocity vectors separately, and it is shown that directed actin motion is found in myosin extracts from single skeletal muscle fibers. The presented approach may prove helpful to identify actin filament subpopulations and to analyze actin-myosin interaction kinetics under biochemical regulation.
我们提出了一种在有噪声的荧光图像序列中计算单物体速度统计量的方法。该算法应用于体外肌动蛋白 - 肌球蛋白运动测定的分子成像数据。我们从小波变换和曲波变换去噪在降噪和物体恢复方面比较了它们的相对效率。结果表明，虽然这两种算法都能有效地降低背景噪声，但曲波去噪能更可靠地恢复肌动蛋白丝的弯曲边缘。使用一种新颖的分割方案明确识别非交叉的时空肌动蛋白轨迹，该方案局部结合了二维和三维分割的信息。最后，通过三维结构张量计算图像序列的光流矢量场，并将其映射到分割后的轨迹上。利用单轨迹统计量，从图像序列中提取的全局速度分布被分解为各个轨迹的贡献。该技术还进一步用于分别分析速度矢量的x和y分量的分布，结果表明在单个骨骼肌纤维的肌球蛋白提取物中发现了有向的肌动蛋白运动。所提出的方法可能有助于识别肌动蛋白丝亚群，并分析生化调节下的肌动蛋白 - 肌球蛋白相互作用动力学。
