Multi scale and slice-based approach for automatic spine detection

Siu Kai Choy; Kun Chen; Yong Zhang; Matthew Baron; Merilee A. Teylan; Yong Kim; Chong Sze TONG; Zhihuan Song; Stephen T.C. Wong

doi:10.1109/IEMBS.2010.5626640

Multi scale and slice-based approach for automatic spine detection

Siu Kai Choy^*, Kun Chen, Yong Zhang, Matthew Baron, Merilee A. Teylan, Yong Kim, Chong Sze TONG, Zhihuan Song, Stephen T.C. Wong

^*Corresponding author for this work

Department of Mathematics

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

4 Citations (Scopus)

Abstract

Dendritic spines play an essential role in the central nervous system. Recent experiments have revealed that neuron functional properties are highly correlated with the statistical and morphological changes of the dendritic spines. In this paper, we propose a new multi scale approach for detecting dendritic spines in a 2D Maximum Intensity Projection (MIP) image of the 3D neuron data stacks collected from a 2-photon laser scanning confocal microscope. The proposed method utilizes the curvilinear structure detector in conjunction with the multi scale spine detection algorithm which automatically and accurately extracts and segments the spines with variational sizes along the dendrite. In addition, a slice-based spine detection algorithm is also proposed to detect spines which are hidden from the MIP image within the dendrite area. Experimental results show that our proposed method is effective for automatic spine detection and is able to accurately segment dendrite.

Original language	English
Title of host publication	2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Pages	4765-4768
Number of pages	4
DOIs	https://doi.org/10.1109/IEMBS.2010.5626640
Publication status	Published - 2010
Event	2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina Duration: 31 Aug 2010 → 4 Sept 2010

Publication series

Name	2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

Conference

Conference	2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Country/Territory	Argentina
City	Buenos Aires
Period	31/08/10 → 4/09/10

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10.1109/IEMBS.2010.5626640

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Choy, S. K., Chen, K., Zhang, Y., Baron, M., Teylan, M. A., Kim, Y., TONG, C. S., Song, Z., & Wong, S. T. C. (2010). Multi scale and slice-based approach for automatic spine detection. In 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 (pp. 4765-4768). Article 5626640 (2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10). https://doi.org/10.1109/IEMBS.2010.5626640

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title = "Multi scale and slice-based approach for automatic spine detection",

abstract = "Dendritic spines play an essential role in the central nervous system. Recent experiments have revealed that neuron functional properties are highly correlated with the statistical and morphological changes of the dendritic spines. In this paper, we propose a new multi scale approach for detecting dendritic spines in a 2D Maximum Intensity Projection (MIP) image of the 3D neuron data stacks collected from a 2-photon laser scanning confocal microscope. The proposed method utilizes the curvilinear structure detector in conjunction with the multi scale spine detection algorithm which automatically and accurately extracts and segments the spines with variational sizes along the dendrite. In addition, a slice-based spine detection algorithm is also proposed to detect spines which are hidden from the MIP image within the dendrite area. Experimental results show that our proposed method is effective for automatic spine detection and is able to accurately segment dendrite.",

author = "Choy, {Siu Kai} and Kun Chen and Yong Zhang and Matthew Baron and Teylan, {Merilee A.} and Yong Kim and TONG, {Chong Sze} and Zhihuan Song and Wong, {Stephen T.C.}",

note = "Copyright: Copyright 2011 Elsevier B.V., All rights reserved.; 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 ; Conference date: 31-08-2010 Through 04-09-2010",

year = "2010",

doi = "10.1109/IEMBS.2010.5626640",

language = "English",

isbn = "9781424441235",

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Choy, SK, Chen, K, Zhang, Y, Baron, M, Teylan, MA, Kim, Y, TONG, CS, Song, Z & Wong, STC 2010, Multi scale and slice-based approach for automatic spine detection. in 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10., 5626640, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10, pp. 4765-4768, 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10, Buenos Aires, Argentina, 31/08/10. https://doi.org/10.1109/IEMBS.2010.5626640

Multi scale and slice-based approach for automatic spine detection. / Choy, Siu Kai; Chen, Kun; Zhang, Yong et al.
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10. 2010. p. 4765-4768 5626640 (2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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T1 - Multi scale and slice-based approach for automatic spine detection

AU - Choy, Siu Kai

AU - Chen, Kun

AU - Zhang, Yong

AU - Baron, Matthew

AU - Teylan, Merilee A.

AU - Kim, Yong

AU - TONG, Chong Sze

AU - Song, Zhihuan

AU - Wong, Stephen T.C.

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N2 - Dendritic spines play an essential role in the central nervous system. Recent experiments have revealed that neuron functional properties are highly correlated with the statistical and morphological changes of the dendritic spines. In this paper, we propose a new multi scale approach for detecting dendritic spines in a 2D Maximum Intensity Projection (MIP) image of the 3D neuron data stacks collected from a 2-photon laser scanning confocal microscope. The proposed method utilizes the curvilinear structure detector in conjunction with the multi scale spine detection algorithm which automatically and accurately extracts and segments the spines with variational sizes along the dendrite. In addition, a slice-based spine detection algorithm is also proposed to detect spines which are hidden from the MIP image within the dendrite area. Experimental results show that our proposed method is effective for automatic spine detection and is able to accurately segment dendrite.

AB - Dendritic spines play an essential role in the central nervous system. Recent experiments have revealed that neuron functional properties are highly correlated with the statistical and morphological changes of the dendritic spines. In this paper, we propose a new multi scale approach for detecting dendritic spines in a 2D Maximum Intensity Projection (MIP) image of the 3D neuron data stacks collected from a 2-photon laser scanning confocal microscope. The proposed method utilizes the curvilinear structure detector in conjunction with the multi scale spine detection algorithm which automatically and accurately extracts and segments the spines with variational sizes along the dendrite. In addition, a slice-based spine detection algorithm is also proposed to detect spines which are hidden from the MIP image within the dendrite area. Experimental results show that our proposed method is effective for automatic spine detection and is able to accurately segment dendrite.

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Choy SK, Chen K, Zhang Y, Baron M, Teylan MA, Kim Y et al. Multi scale and slice-based approach for automatic spine detection. In 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10. 2010. p. 4765-4768. 5626640. (2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10). doi: 10.1109/IEMBS.2010.5626640

Multi scale and slice-based approach for automatic spine detection

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