Automatic markup of neural cell membranes using boosted decision stumps

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Publication Type Journal Article
School or College College of Engineering
Department Electrical & Computer Engineering
Creator Tasdizen, Tolga
Other Author Venkataraju, Kannan Umadevi; Paiva, Antonio R. C.; Jurrus, Elizabeth
Title Automatic markup of neural cell membranes using boosted decision stumps
Date 2009
Description To better understand the central nervous system, neurobiologists need to reconstruct the underlying neural circuitry from electron microscopy images. One of the necessary tasks is to segment the individual neurons. For this purpose, we propose a supervised learning approach to detect the cell membranes. The classifier was trained using AdaBoost, on local and context features. The features were selected to highlight the line characteristics of cell membranes. It is shown that using features from context positions allows for more information to be utilized in the classification. Together with the nonlinear discrimination ability of the AdaBoost classifier, this results in clearly noticeable improvements over previously used methods.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
First Page 1039
Last Page 1042
Language eng
Bibliographic Citation Venkataraju, K.. U., Paiva, A.R. C., Jurrus, E., & Tasdizen, T. (2009). Automatic markup of neural cell membranes using boosted decision stumps. IEEE International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, 1039-42.
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Format Medium application/pdf
Format Extent 834,820 bytes
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Reference URL https://collections.lib.utah.edu/ark:/87278/s64b3jj4