Multi-scale segmentation of neurons based on one-class classification
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- 作者：Paul Hernandez-Herreraa ; phernandez7@uh.edu" class="auth_mail" title="E-mail the corresponding author ; Manos Papadakisa ; b ; Ioannis A. Kakadiarisa
- 关键词：Neuron tracing ; Segmentation ; One-class classification
- 刊名：Journal of Neuroscience Methods
- 出版年：2016
- 出版时间：15 June 2016
- 年：2016
- 卷：266
- 期：Complete
- 页码：94-106
- 全文大小：5540 K
文摘
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A multi-scale framework to segment the neurons.
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A mathematically rigorous general approach for the normalization of the response of a multi-scale ensemble of linear filters.
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A multi-scale framework to compute the Laplacian of the 3D image stack and an approach to compute as many decision functions as the number of scales (one for each scale) used for segmentation.
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A mathematical justification for using different low-pass filters to compute the Laplacian and the Hessian matrix.
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An extensive experimental evaluation of the performance of our approach on a number of datasets, including all of the DIADEM competition.