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Abstract
The digital reconstruction of single neurons from 3D confocal microscopic images is an important tool for understanding the neuron morphology and function. However the accurate automatic neuron reconstruction remains a challenging task due to the varying image quality and the complexity in the neuronal arborisation. Targeting the common challenges of neuron tracing, we propose a novel automatic 3D neuron reconstruction algorithm, named Rivulet, which is based on the multi-stencils fast-marching and iterative back-tracking. The proposed Rivulet algorithm is capable of tracing discontinuous areas without being interrupted by densely distributed noises. By evaluating the proposed pipeline with the data provided by the Diadem challenge and the recent BigNeuron project, Rivulet is shown to be robust to challenging microscopic imagestacks. We discussed the algorithm design in technical details regarding the relationships between the proposed algorithm and the other state-of-the-art neuron tracing algorithms.
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Affiliation(s)
- Siqi Liu
- School of Information Technologies, University of Sydney, Darlington, NSW, Australia.
| | - Donghao Zhang
- School of Information Technologies, University of Sydney, Darlington, NSW, Australia
| | - Sidong Liu
- School of Information Technologies, University of Sydney, Darlington, NSW, Australia
| | - Dagan Feng
- School of Information Technologies, University of Sydney, Darlington, NSW, Australia
| | | | - Weidong Cai
- School of Information Technologies, University of Sydney, Darlington, NSW, Australia.
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Lacoste B, Comin CH, Ben-Zvi A, Kaeser PS, Xu X, Costa LDF, Gu C. Sensory-related neural activity regulates the structure of vascular networks in the cerebral cortex. Neuron 2014; 83:1117-30. [PMID: 25155955 DOI: 10.1016/j.neuron.2014.07.034] [Citation(s) in RCA: 111] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/18/2014] [Indexed: 11/15/2022]
Abstract
Neurovascular interactions are essential for proper brain function. While the effect of neural activity on cerebral blood flow has been extensively studied, whether or not neural activity influences vascular patterning remains elusive. Here, we demonstrate that neural activity promotes the formation of vascular networks in the early postnatal mouse barrel cortex. Using a combination of genetics, imaging, and computational tools to allow simultaneous analysis of neuronal and vascular components, we found that vascular density and branching were decreased in the barrel cortex when sensory input was reduced by either a complete deafferentation, a genetic impairment of neurotransmitter release at thalamocortical synapses, or a selective reduction of sensory-related neural activity by whisker plucking. In contrast, enhancement of neural activity by whisker stimulation led to an increase in vascular density and branching. The finding that neural activity is necessary and sufficient to trigger alterations of vascular networks reveals an important feature of neurovascular interactions.
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Affiliation(s)
- Baptiste Lacoste
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Cesar H Comin
- IFSC, University of Sao Paulo, Sao Carlos, SP, Brazil
| | - Ayal Ben-Zvi
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Pascal S Kaeser
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Xiaoyin Xu
- Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Chenghua Gu
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
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Comin CH, da Fontoura Costa L. Shape, connectedness and dynamics in neuronal networks. J Neurosci Methods 2013; 220:100-15. [PMID: 23954264 DOI: 10.1016/j.jneumeth.2013.08.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2013] [Revised: 08/01/2013] [Accepted: 08/02/2013] [Indexed: 10/26/2022]
Abstract
The morphology of neurons is directly related to several aspects of the nervous system, including its connectedness, health, development, evolution, dynamics and, ultimately, behavior. Such interplays of the neuronal morphology can be understood within the more general shape-function paradigm. The current article reviews, in an introductory way, some key issues regarding the role of neuronal morphology in the nervous system, with emphasis on works developed in the authors' group. The following topics are addressed: (a) characterization of neuronal shape; (b) stochastic synthesis of neurons and neuronal systems; (c) characterization of the connectivity of neuronal networks by using complex networks concepts; and (d) investigations of influences of neuronal shape on network dynamics. The presented concepts and methods are useful also for several other multiple object systems, such as protein-protein interaction, tissues, aggregates and polymers.
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Affiliation(s)
- Cesar Henrique Comin
- Instituto de Física de São Carlos, Universidade de São Paulo, São Carlos, SP, Caixa Postal 369, 13560-970, Brazil.
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5
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Abstract
The study of the structure and function of neuronal cells and networks is of crucial importance in the endeavor to understand how the brain works. A key component in this process is the extraction of neuronal morphology from microscopic imaging data. In the past four decades, many computational methods and tools have been developed for digital reconstruction of neurons from images, with limited success. As witnessed by the growing body of literature on the subject, as well as the organization of challenging competitions in the field, the quest for a robust and fully automated system of more general applicability still continues. The aim of this work, is to contribute by surveying recent developments in the field for anyone interested in taking up the challenge. Relevant aspects discussed in the article include proposed image segmentation methods, quantitative measures of neuronal morphology, currently available software tools for various related purposes, and morphology databases. (c) 2010 International Society for Advancement of Cytometry.
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Affiliation(s)
- Erik Meijering
- Biomedical Imaging Group Rotterdam, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands
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Yuan X, Trachtenberg JT, Potter SM, Roysam B. MDL constrained 3-D grayscale skeletonization algorithm for automated extraction of dendrites and spines from fluorescence confocal images. Neuroinformatics 2009; 7:213-32. [PMID: 20012509 DOI: 10.1007/s12021-009-9057-y] [Citation(s) in RCA: 42] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2008] [Accepted: 10/30/2009] [Indexed: 11/27/2022]
Abstract
This paper presents a method for improved automatic delineation of dendrites and spines from three-dimensional (3-D) images of neurons acquired by confocal or multi-photon fluorescence microscopy. The core advance presented here is a direct grayscale skeletonization algorithm that is constrained by a structural complexity penalty using the minimum description length (MDL) principle, and additional neuroanatomy-specific constraints. The 3-D skeleton is extracted directly from the grayscale image data, avoiding errors introduced by image binarization. The MDL method achieves a practical tradeoff between the complexity of the skeleton and its coverage of the fluorescence signal. Additional advances include the use of 3-D spline smoothing of dendrites to improve spine detection, and graph-theoretic algorithms to explore and extract the dendritic structure from the grayscale skeleton using an intensity-weighted minimum spanning tree (IW-MST) algorithm. This algorithm was evaluated on 30 datasets organized in 8 groups from multiple laboratories. Spines were detected with false negative rates less than 10% on most datasets (the average is 7.1%), and the average false positive rate was 11.8%. The software is available in open source form.
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Affiliation(s)
- Xiaosong Yuan
- Jonsson Engineering Center, Center for Subsurface Sensing & Imaging Systems, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
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Ristanović D, Stefanović B, Milošević N, Grgurević M, Stanković J. Mathematical modeling and computational analysis of neuronal cell images: Application to dendritic arborization of Golgi-impregnated neurons in dorsal horns of the rat spinal cord. Neurocomputing 2006. [DOI: 10.1016/j.neucom.2005.04.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Abstract
This article addresses the issues of neural shape characterization and analysis from the perspective of one of the main roles played by neural shapes, namely, connectivity. This study is oriented toward the geometry at the individual cell level and involves the use of the percolation concept from statistical mechanics, which is reviewed in an accessible fashion. The characterization of the neural cell geometry with respect to connectivity is performed in terms of critical percolation probability obtained experimentally while considering several types of geometrical interactions between cells, therefore directly expressing the potential for connections defined by each situation. Two basic situations are considered: dendrite-dendrite and dendrite-axon interactions. The obtained results corroborate the potential of the critical percolation probability as a valuable resource for characterizing, classifying, and analyzing the morphology of neural cells.
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Kimler VA, Tracy-Bee M, Ollie CD, Langer RM, Montante JM, Marks CRC, Carl Freeman D, Anton Hough R, Taylor JD. Characterization of Melanophore Morphology by Fractal Dimension Analysis. ACTA ACUST UNITED AC 2004; 17:165-72. [PMID: 15016306 DOI: 10.1046/j.1600-0749.2003.00125.x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Fractal or focal dimension (FD) analysis is a valuable tool to identify physiologic stimuli at the cellular and tissue levels that allows for quantification of cell perimeter complexity. The FD analysis was determined on fluorescence images of caffeine- or epinephrine-treated (or untreated control) killifish Fundulus heteroclitus (Linneaus) melanophores in culture. Cell perimeters were indicated by rhodamine-phalloidin labeling of cortical microfilaments using box-counting FD analysis. Caffeine-treated melanophores displayed dispersed melanosomes in cells with less serrated edges and reduced FD and complexity. Complexity in epinephrine-treated cells was significantly higher than the caffeine-treated cells or in the control. Cytoarchitectural variability of the cell perimeter is expected because cells change shape when cued with agents. Epinephrine-treated melanophores demonstrated aggregated melanosomes in cells with more serrated edges, significantly higher FD and thus complexity. Melanophores not treated with caffeine or epinephrine produced variable distributions of melanosomes and resulted in cells with variably serrated edges and intermediate FD with a larger SE of the regression and greater range of complexity. Dispersion of melanosomes occurs with rearrangements of the cytoskeleton to accommodate centrifugal distribution of melanosomes throughout the cell and to the periphery. The loading of melanosomes onto cortical microfilaments may provide a less complex cell contour, with the even distribution of the cytoskeleton and melanosomes. Aggregation of melanosomes occurs with rearrangements of the cytoskeleton to accommodate centripetal distribution of melanosomes. The aggregation of melanosomes may contribute to centripetal retraction of the cytoskeleton and plasma membrane. The FD analysis is, therefore, a convenient method to measure contrasting morphologic changes within stimulated cells.
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Affiliation(s)
- Victoria A Kimler
- Biology Department, College of Engineering and Science, University of Detroit Mercy, Detroit, MI, USA.
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Li Z, Da F Costa L. INVESTIGATING SHAPE AND FUNCTION RELATIONSHIP IN RETINAL GANGLION CELLS. J Integr Neurosci 2002; 1:195-215. [PMID: 15011285 DOI: 10.1142/s0219635202000098] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2002] [Accepted: 08/10/2002] [Indexed: 11/18/2022] Open
Abstract
This article addresses the investigation of the relationship between neural shape and function in cat retinal ganglion cells in terms of representative morphological features. More specifically, a series of geometrical measures is extracted from two-dimensional images of these cells, and pattern recognition methods are applied in order to quantify the differentiation between the two classes (i.e., alpha, beta). The morphological measures cover several of the more meaningful geometrical features of neuronal cells, including: (a) the distribution of angles along the cell contours considering several smoothing degrees; (b) the overall interaction between the cell arborization and the surrounding space, quantified in terms of the multiscale fractal dimension; and (c) the distribution of width and extent of the dendritic processes. Several combinations of such morphological measures are assessed with respect to the separability of the classes. The obtained results indicate that the methods based on statistic relation between segment length and segment diameter, and the method of multiscale angle entropy not only successfully encapsulated a large amount of experimental data into relatively compact patterns but also marked off various ganglion cells into befit groups. On the other hand, the method of neuron classification based on fractal dimension resulted relatively less effective for class separation.
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Affiliation(s)
- Zhaohui Li
- Cybernetic Vision Research Group, IFSC, University of São Paulo, Caixa Postal 369, São Carlos, SP, 13560-970, Brazil.
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Coelho RC, Gesù VD, Bosco GL, Tanaka JS, Valenti C. Shape-Based Features for Cat Ganglion Retinal Cells Classification. ACTA ACUST UNITED AC 2002; 8:213-26. [DOI: 10.1006/rtim.2002.0281] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Dima A, Scholz M, Obermayer K. Automatic segmentation and skeletonization of neurons from confocal microscopy images based on the 3-D wavelet transform. IEEE Trans Image Process 2002; 11:790-801. [PMID: 18244675 DOI: 10.1109/tip.2002.800888] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
In this work, we focus on methods for the preprocessing of neurons from three-dimensional (3-D) confocal microscopy images, which are needed for a subsequent detailed morphologic analysis. Due to the specific image properties of confocal microscopy scans, we had to include several heuristic approaches which are based on multiscale edges to guarantee meaningful results: (1) a reliable segmentation of objects of different sizes independent of image contrast, and, based on it, (2) the computation of skeleton points along the branch central axes, and (3) the reliable detection of branching points and of problematic regions. These are preprocessing steps to gather information which is needed by the subsequent construction of a graph representing the geometry of the neuron and a final surface reconstruction.
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Affiliation(s)
- Anca Dima
- Technische Universität Berlin, D-10587 Berlin, Germany.
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