2019
DOI: 10.1101/864587
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

3dSpAn: An interactive software for 3D segmentation and analysis of dendritic spines

Abstract: Background: 3D segmentation and analysis of dendritic spines involve two major challenges: 1) how to segment individual spines in 3D from the dendrites and 2) how to quantitatively assess the 3D morphology of individual spines. We developed software named 3dSpAn to address these two issues by implementing a 3D multiscale opening algorithm in shared intensity space and using effective morphological features, for individual dendritic spine plasticity analysis.Results: 3dSpAn works in four main modules: Preproces… Show more

Help me understand this report
View published versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
3
0

Year Published

2020
2020
2021
2021

Publication Types

Select...
1
1

Relationship

1
1

Authors

Journals

citations
Cited by 2 publications
(3 citation statements)
references
References 32 publications
0
3
0
Order By: Relevance
“…The diversity of images and a presence of artifacts is the major obstacle for using fully automatic segmentation algorithms, which often require setting the parameters controlling the segmentation according to data modalities and might be insufficiently flexible to cope with complicated structures [ 151 ]. Thus, many analyses are based on manual or semi-manual processing of images [ 152 ]. Several methods based on conventional/deep machine learning have recently been reported for automatic segmentation and analysis of dendritic spines [ 153 , 154 , 155 ].…”
Section: Experimental Methodologymentioning
confidence: 99%
See 1 more Smart Citation
“…The diversity of images and a presence of artifacts is the major obstacle for using fully automatic segmentation algorithms, which often require setting the parameters controlling the segmentation according to data modalities and might be insufficiently flexible to cope with complicated structures [ 151 ]. Thus, many analyses are based on manual or semi-manual processing of images [ 152 ]. Several methods based on conventional/deep machine learning have recently been reported for automatic segmentation and analysis of dendritic spines [ 153 , 154 , 155 ].…”
Section: Experimental Methodologymentioning
confidence: 99%
“…The most popular software tools that were reported in experimental protocols to be used for spines segmentation and analysis are SpineMagick (patent no. WO/2013/021001), 3dSpAn [ 152 ], Neurolucida [ 156 ], SpineLab [ 157 ], Imaris Editing Tools of FilamentTracer [ 158 ], NeuronIQ [ 159 ], MetaMorph [ 160 ], 3DMA-Neuron [ 161 ], NeuronStudio [ 162 ].…”
Section: Experimental Methodologymentioning
confidence: 99%
“…SpineJ 22 is a recently released good alternative for super-resolution microscopy image stacks but whether it would work for CLSM or 2PLSM images is an open question and it does not offer time-series analysis. 2dSpAn 23 and its 3D version 3dSpAn 24,25 are two other alternative available software packages for morphological analysis of dendritic spines. Although these software packages are providing good results, they also do not offer longitudinal analysis and do not allow for manual correction, and either report spine head and neck volume together as one entity or the total length of the spine head from the tip to base, neither of which have reported biological correlates.…”
Section: Introductionmentioning
confidence: 99%