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An Automatic Neuron Tracing Method Based on Mean Shift and Minimum Spanning Tree

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Brain Informatics and Health (BIH 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9919))

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Abstract

Digital reconstruction of 3D neuron structures is an important step toward reverse engineering the wiring and functions of a brain. Toward this end, the BigNeuron project bench testing was launched to gather a worldwide community to establish a Big Data resource and a set of the state-of-the-art of single neuron reconstruction algorithms for neuroscience community. As one of the communities, we contribute a Mean shift and Minimum Spanning Tree (M-MST) algorithm to trace single neuron morphology. In our experiment, we have successfully reconstructed 120 Drosophila neurons by using the M-MST algorithm and achieved relatively good difference scores compared with other four algorithms by using APP2 as a reference object.

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Acknowledgements

This work was funded by National Basic Research Program of China (2014CB744600), International Science & Technology Cooperation Program of China (2013DFA32180), National Natural Science Foundation of China (61420106005, 61272345), and JSPS Grants-in-Aid for Scientific Research of Japan (26350994), and supported by Beijing Municipal Commission of Education, and Beijing Xuanwu Hospital.

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Correspondence to Zhijiang Wan .

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Wan, Z., He, Y., Hao, M., Yang, J., Zhong, N. (2016). An Automatic Neuron Tracing Method Based on Mean Shift and Minimum Spanning Tree. In: Ascoli, G., Hawrylycz, M., Ali, H., Khazanchi, D., Shi, Y. (eds) Brain Informatics and Health. BIH 2016. Lecture Notes in Computer Science(), vol 9919. Springer, Cham. https://doi.org/10.1007/978-3-319-47103-7_4

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  • DOI: https://doi.org/10.1007/978-3-319-47103-7_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47102-0

  • Online ISBN: 978-3-319-47103-7

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