Neurondynamics: A method for neurotransmitter vesicle movement characterization in neurons

F. Carpinteiro, Pedro Costa, Mario Sáenz Espinoza, Ivo M. Silva, J. Cunha
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引用次数: 2

Abstract

Automated tracking of axonal neurotransmitter vesicles is a challenging problem in neuroscience. The present vesicle tracking is typically performed manually over confocal microscopy images. NeuronDynamics is a method designed to automate and speed-up the characterization of global vesicle movement in neurons while yielding high accuracy and precision results (similar or better than expert clinicians). For a set of fluorescent-marked vesicles “films”, Neuron-Dynamics performs a two stage approach: 1) Training: the system asks the user to mark a set of vesicles and the position of the cellular body; 2) Detection & tracking: based on the previous training, the system runs a Bayesian classifier over the image sequence to detect and classify vesicles and their movements (speed and direction). The obtained results were compared to another state-of-the-art method (FluoTracker), and were found greatly higher in accuracy, sensitivity, specificity and precision. Although NeuronDynamics is a semi-automated process, it is significantly faster than manual tracking and can be adapted to be used for similar approaches for other biological samples.
神经动力学:神经递质囊泡运动表征的一种方法
轴突神经递质囊泡的自动跟踪是神经科学中的一个具有挑战性的问题。目前的囊泡跟踪通常是在共聚焦显微镜图像上手动进行的。NeuronDynamics是一种旨在自动化和加速神经元全局囊泡运动表征的方法,同时产生高精度和精密度结果(类似或优于专家临床医生)。对于一组荧光标记的囊泡“薄膜”,Neuron-Dynamics执行两个阶段的方法:1)训练:系统要求用户标记一组囊泡和细胞体的位置;2)检测与跟踪:在之前训练的基础上,系统在图像序列上运行贝叶斯分类器,对囊泡及其运动(速度和方向)进行检测和分类。所获得的结果与另一种最先进的方法(FluoTracker)进行了比较,发现准确度、灵敏度、特异性和精密度大大提高。虽然NeuronDynamics是一个半自动化的过程,但它比手动跟踪要快得多,并且可以适应用于其他生物样品的类似方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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