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Activity Number:
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514
- Recent Advances in Imaging Statistics: Bayesian Methods and Beyond
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Type:
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Contributed
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Date/Time:
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Wednesday, August 2, 2017 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Imaging
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Abstract #323604
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Title:
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Automated Tracking of Neuronal Outgrowth by Markov Chain Monte Carlo
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Author(s):
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Alvason Li* and Larry Corey and Jia Zhu
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Companies:
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Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center
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Keywords:
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Markov chain ;
GPU ;
Neurite ;
Image ;
CUDA
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Abstract:
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Neuronal structure and outgrowth is involved in a wide range of extracellular stimuli and illnesses. However, neurite outgrowth and precise quantification is a challenging task that only cutting-edge image analysis techniques can be performed with success and reliability. A new and effective Python package for automated tracking of neuronal outgrowth is developed in the stochastic framework. First, it designs efficient CPU-based Markov Chain algorithm to explore the complex neuronal outgrowth. Then, a ultra fast GPU-based Markov Chain algorithm is developed to quantify extensive amount of neurite images for studying the behavior of neuron under stimuli.
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Authors who are presenting talks have a * after their name.
