8 February 2017 An automated detection for axonal boutons in vivo two-photon imaging of mouse
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Proceedings Volume 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016); 102250Q (2017) https://doi.org/10.1117/12.2267573
Event: Eighth International Conference on Graphic and Image Processing, 2016, Tokyo, Japan
Abstract
Activity-dependent changes in the synaptic connections of the brain are tightly related to learning and memory. Previous studies have shown that essentially all new synaptic contacts were made by adding new partners to existing synaptic elements. To further explore synaptic dynamics in specific pathways, concurrent imaging of pre and postsynaptic structures in identified connections is required. Consequently, considerable attention has been paid for the automated detection of axonal boutons. Different from most previous methods proposed in vitro data, this paper considers a more practical case in vivo neuron images which can provide real time information and direct observation of the dynamics of a disease process in mouse. Additionally, we present an automated approach for detecting axonal boutons by starting with deconvolving the original images, then thresholding the enhanced images, and reserving the regions fulfilling a series of criteria. Experimental result in vivo two-photon imaging of mouse demonstrates the effectiveness of our proposed method.
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Weifu Li, Dandan Zhang, Qiwei Xie, Xi Chen, Hua Han, "An automated detection for axonal boutons in vivo two-photon imaging of mouse", Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102250Q (8 February 2017); doi: 10.1117/12.2267573; https://doi.org/10.1117/12.2267573
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