Journal article
3dSpAn: An interactive software for 3D segmentation and analysis of dendritic spines
Neuroinformatics (Totowa, N.J.), Vol.20(3), pp.679-698
07/2022
DOI: 10.1007/s12021-021-09549-0
Abstract
Three-dimensional segmentation and analysis of dendritic spine morphology involve two major challenges: 1) how to segment individual spines from the dendrites and 2) how to quantitatively assess the morphology of individual spines. To address these two issues, we developed software called 3dSpAn (3-dimensional Spine Analysis), based on implementing a previously published method, 3D multi-scale opening algorithm in shared intensity space. 3dSpAn consists of four modules: a) Preprocessing and Region of Interest (ROI) selection, b) Intensity thresholding and seed selection, c) Multi-scale segmentation, and d) Quantitative morphological feature extraction. In this article, we present the results of segmentation and morphological analysis for different observation methods and conditions, including in vitro and ex vivo imaging with confocal microscopy, and in vivo observations using high-resolution two-photon microscopy. In particular, we focus on software usage, the influence of adjustable parameters on the obtained results, user reproducibility, accuracy analysis, and also include a qualitative comparison with a commercial benchmark. 3dSpAn software is freely available for non-commercial use at www.3dSpAn.org.
Details
- Title: Subtitle
- 3dSpAn: An interactive software for 3D segmentation and analysis of dendritic spines
- Creators
- Nirmal Das - Jadavpur UniversityEwa Baczynska - Nencki Institute of Experimental BiologyMonika Bijata - Nencki Institute of Experimental BiologyBlazej Ruszczycki - Nencki Institute of Experimental BiologyAndre Zeug - Medizinische Hochschule HannoverDariusz Plewczynski - Warsaw University of TechnologyPunam Kumar Saha - University of IowaEvgeni Ponimaskin - Medizinische Hochschule HannoverJakub Wlodarczyk - Nencki Institute of Experimental BiologySubhadip Basu - Jadavpur University
- Resource Type
- Journal article
- Publication Details
- Neuroinformatics (Totowa, N.J.), Vol.20(3), pp.679-698
- DOI
- 10.1007/s12021-021-09549-0
- ISSN
- 1539-2791
- eISSN
- 1559-0089
- Grant note
- name: Department of Biotechnology, India, award: BT/PR16356/BID/7/596/2016; DOI: 10.13039/501100004281, name: Polish National Science Centre, award: 2017/26/E/NZ4/00637; name: CSIR SRF Direct Fellowship, India, award: 09|096(0921)2K18 EMR-I; DOI: 10.13039/501100004281, name: Polish National Science Centre, award: UMO-2017/27/N/NZ3/02417; DOI: 10.13039/501100001870, name: Foundation for Polish Science, award: POIR.04.04.00-00-43BC/17-00; DOI: 10.13039/501100004281, name: Polish National Science Centre, award: 2019/35/O/ST6/02484, 2014/15/B/ST6/05082; name: Deutsche Forschungsgemeinschaft Grant, award: PO732; name: Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund; name: National Institute of Health, USA, award: 1U54DK107967-01
- Language
- English
- Electronic publication date
- 11/07/2021
- Date published
- 07/2022
- Academic Unit
- Radiology; Electrical and Computer Engineering
- Record Identifier
- 9984197913702771
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