Detection of spontaneous vesicle release at individual synapses using multiple wavelets in a CWT-Based algorithm

Authors:
Stefan Sokoll;Klaus Tönnies;Martin Heine
Affiliations:
Group Molecular Physiology, Leibniz Inst. for Neurobiology, Magdeburg, Germany, Dept. of Simulation and Graphics, Otto-von-Guericke Univ., Magdeburg, Germany;Dept. of Simulation and Graphics, Otto-von-Guericke Univ., Magdeburg, Germany;Group Molecular Physiology, Leibniz Inst. for Neurobiology, Magdeburg, Germany
Venue:
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Year:
2012

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Abstract

In this paper we present an algorithm for the detection of spontaneous activity at individual synapses in microscopy images. By employing the optical marker pHluorin, we are able to visualize synaptic vesicle release with a spatial resolution in the nm range in a non-invasive manner. We compute individual synaptic signals from automatically segmented regions of interest and detect peaks that represent synaptic activity using a continuous wavelet transform based algorithm. As opposed to standard peak detection algorithms, we employ multiple wavelets to match all relevant features of the peak. We evaluate our multiple wavelet algorithm (MWA) on real data and assess the performance on synthetic data over a wide range of signal-to-noise ratios.