3D dendrite reconstruction and spine identification

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Abstract

In neuron-biology, 3D neuron dendrite reconstruction followed by spine identification is indispensable for the study of neuronal functions and biophysical properties. In this paper, we propose an automatic dendrite reconstruction method to with a surface representation of the neuron on the basis of a novel level set approach. Our novel level set approach can effectively tackle the problem of segmentation under blurring and intensity in-homogeneity. Then spines are detected based on dendrite medial axis and a label-based thinning strategy is proposed to accurately extract the dendrite skeleton for spine identification. Experimental results reveal that our method works well. © 2008 Springer Berlin Heidelberg.

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APA

Zhou, W., Li, H., & Zhou, X. (2008). 3D dendrite reconstruction and spine identification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5242 LNCS, pp. 18–26). Springer Verlag. https://doi.org/10.1007/978-3-540-85990-1_3

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