Multiple particle tracking in 3-D+t microscopy: Method and application to the tracking of endocytosed quantum dots
Multiple particle tracking in 3-D+t microscopy: Method and application to the tracking of endocytosed quantum dots
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DOI：
10.1109/tip.2006.872323
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发表时间：
2006-05-01
影响因子：
10.6
通讯作者：
Olivo-Marin, JC
中科院分区：
文献类型：
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作者：
Genovesio, A;Liedl, T;Olivo-Marin, JC
我们提出了一种检测和跟踪多个移动生物点状颗粒的方法，这些颗粒在通过多维荧光显微镜获取的图像序列中显示出不同类型的动态。它能够提取和分析信息，例如内体颗粒的数量、位置、速度、运动和扩散阶段。该方法由几个阶段组成。在通过三维 (3-D) 未抽取小波变换执行检测阶段后，我们针对每个检测到的点计算其在下一帧中的未来状态的多个预测。这是通过交互多模型 (IMM) 算法实现的，该算法包括与不同的生物真实运动类型相对应的多个模型。此后，通过基于每个 IMM 似然性最大化的数据关联算法来构建轨迹。最后阶段包括更新 IMM 滤波器，以便计算当前图像的最终估计并改进对下一个图像的预测。该方法的性能在合成图像数据上进行了验证，并用于表征包含量子点的内吞囊泡的 3-D 运动。
We propose a method to detect and track multiple moving biological spot-like particles showing different kinds of dynamics in image sequences acquired through multidimensional fluorescence microscopy. It enables the extraction and analysis of information such as number, position, speed, movement, and diffusion phases of, e.g., endosomal particles. The method consists of several stages. After a detection stage performed by a three-dimensional (3-D) undecimated wavelet transform, we compute, for each detected spot, several predictions of its future state in the next frame. This is accomplished thanks to an interacting multiple model (IMM) algorithm which includes several models corresponding to different biologically realistic movement types. Tracks are constructed, thereafter, by a data association algorithm based on the maximization of the likelihood of each IMM. The last stage consists of updating the IMM filters in order to compute final estimations for the present image and to improve predictions for the next image. The performances of the method are validated on synthetic image data and used to characterize the 3-D movement of endocytic vesicles containing quantum dots.