Das Nirmal, Baczynska Ewa, Bijata Monika, Ruszczycki Blazej, Zeug Andre, Plewczynski Dariusz, Saha Punam Kumar, Ponimaskin Evgeni, Wlodarczyk Jakub, Basu Subhadip
Department of CSE, Jadavpur University, 188 Raja S.C. Mullick Road, Kolkata, 700032, India.
Department of CSE, School of Engineering and Technology, Adamas University, Barbaria, Kolkata, West Bengal, 700126, India.
Neuroinformatics. 2022 Jul;20(3):679-698. doi: 10.1007/s12021-021-09549-0. Epub 2021 Nov 7.
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 .
1）如何从树突中分割出单个棘突；2）如何定量评估单个棘突的形态。为解决这两个问题，我们基于在共享强度空间中实现先前发表的方法——三维多尺度开放算法，开发了名为3dSpAn（三维棘突分析）的软件。3dSpAn由四个模块组成：a）预处理和感兴趣区域（ROI）选择；b）强度阈值处理和种子选择；c）多尺度分割；d）定量形态特征提取。在本文中，我们展示了不同观察方法和条件下的分割及形态分析结果，包括共聚焦显微镜的体外和离体成像，以及使用高分辨率双光子显微镜的体内观察。特别地，我们重点关注软件使用、可调参数对所得结果的影响、用户可重复性、准确性分析，还包括与商业基准的定性比较。3dSpAn软件可在www.3dSpAn.org上免费用于非商业用途。
