Tracking multiple particles in fluorescence time-lapse microscopy images via probabilistic data association.
Tracking multiple particles in fluorescence time-lapse microscopy images via probabilistic data association.
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DOI：
10.1109/tmi.2014.2359541
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发表时间：
2015-02-01
影响因子：
10.6
通讯作者：
Rohr, Karl
中科院分区：
文献类型：
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作者：
Godinez, William J;Rohr, Karl
跟踪亚细胞结构以及在荧光显微镜图像中显示为“颗粒”的病毒结构产生关于潜在动力学过程的定量信息。我们开发了一种基于概率数据关联的多荧光粒子跟踪方法。该方法结合了一个本地化计划，使用自下而上的战略的基础上的现场增强过滤器，以及自上而下的战略的基础上，使用高斯概率分布计算的卡尔曼滤波器的椭圆形采样方案。定位方案产生多个测量值，这些测量值通过组合创新被并入卡尔曼滤波器，其中关联概率被解释为使用图像似然计算的权重。为了跟踪非常接近的对象，我们计算每个图像位置相对于被跟踪对象的相邻对象的支持度，并使用该支持度来重新计算权重。为了科普多个运动模型，我们集成了交互式多模型算法。该方法已成功地应用于合成的2-D和3-D图像以及真实的2-D和3-D显微图像，并已量化的性能。此外，该方法已成功地应用于2012年IEEE国际生物医学成像研讨会（ISBI）的粒子跟踪挑战赛的2-D和3-D图像数据。
Tracking subcellular structures as well as viral structures displayed as 'particles' in fluorescence microscopy images yields quantitative information on the underlying dynamical processes. We have developed an approach for tracking multiple fluorescent particles based on probabilistic data association. The approach combines a localization scheme that uses a bottom-up strategy based on the spot-enhancing filter as well as a top-down strategy based on an ellipsoidal sampling scheme that uses the Gaussian probability distributions computed by a Kalman filter. The localization scheme yields multiple measurements that are incorporated into the Kalman filter via a combined innovation, where the association probabilities are interpreted as weights calculated using an image likelihood. To track objects in close proximity, we compute the support of each image position relative to the neighboring objects of a tracked object and use this support to recalculate the weights. To cope with multiple motion models, we integrated the interacting multiple model algorithm. The approach has been successfully applied to synthetic 2-D and 3-D images as well as to real 2-D and 3-D microscopy images, and the performance has been quantified. In addition, the approach was successfully applied to the 2-D and 3-D image data of the recent Particle Tracking Challenge at the IEEE International Symposium on Biomedical Imaging (ISBI) 2012.