Literature DB >> 35153709

PyNeval: A Python Toolbox for Evaluating Neuron Reconstruction Performance.

Han Zhang1,2, Chao Liu1,2, Yifei Yu3, Jianhua Dai4, Ting Zhao5, Nenggan Zheng1,3,4.   

Abstract

Quality assessment of tree-like structures obtained from a neuron reconstruction algorithm is necessary for evaluating the performance of the algorithm. The lack of user-friendly software for calculating common metrics motivated us to develop a Python toolbox called PyNeval, which is the first open-source toolbox designed to evaluate reconstruction results conveniently as far as we know. The toolbox supports popular metrics in two major categories, geometrical metrics and topological metrics, with an easy way to configure custom parameters for each metric. We tested the toolbox on both synthetic data and real data to show its reliability and robustness. As a demonstration of the toolbox in real applications, we used the toolbox to improve the performance of a tracing algorithm successfully by integrating it into an optimization procedure.
Copyright © 2022 Zhang, Liu, Yu, Dai, Zhao and Zheng.

Entities:  

Keywords:  PyNeval; metric; neuron reconstruction; neuron tracing; quantitative analysis; toolbox

Year:  2022        PMID: 35153709      PMCID: PMC8831325          DOI: 10.3389/fninf.2021.767936

Source DB:  PubMed          Journal:  Front Neuroinform        ISSN: 1662-5196            Impact factor:   4.081


  13 in total

1.  Proof-editing is the bottleneck of 3D neuron reconstruction: the problem and solutions.

Authors:  Hanchuan Peng; Fuhui Long; Ting Zhao; Eugene Myers
Journal:  Neuroinformatics       Date:  2011-09

2.  An on-line archive of reconstructed hippocampal neurons.

Authors:  R C Cannon; D A Turner; G K Pyapali; H V Wheal
Journal:  J Neurosci Methods       Date:  1998-10-01       Impact factor: 2.390

3.  A broadly applicable 3-D neuron tracing method based on open-curve snake.

Authors:  Yu Wang; Arunachalam Narayanaswamy; Chia-Ling Tsai; Badrinath Roysam
Journal:  Neuroinformatics       Date:  2011-09

Review 4.  Automated Neuron Tracing Methods: An Updated Account.

Authors:  Ludovica Acciai; Paolo Soda; Giulio Iannello
Journal:  Neuroinformatics       Date:  2016-10

5.  BigNeuron: Large-Scale 3D Neuron Reconstruction from Optical Microscopy Images.

Authors:  Hanchuan Peng; Michael Hawrylycz; Jane Roskams; Sean Hill; Nelson Spruston; Erik Meijering; Giorgio A Ascoli
Journal:  Neuron       Date:  2015-07-15       Impact factor: 17.173

6.  NetMets: software for quantifying and visualizing errors in biological network segmentation.

Authors:  David Mayerich; Chris Bjornsson; Jonathan Taylor; Badrinath Roysam
Journal:  BMC Bioinformatics       Date:  2012-05-18       Impact factor: 3.169

7.  Digital reconstructions of neuronal morphology: three decades of research trends.

Authors:  Maryam Halavi; Kelly A Hamilton; Ruchi Parekh; Giorgio A Ascoli
Journal:  Front Neurosci       Date:  2012-04-23       Impact factor: 4.677

8.  neuTube 1.0: A New Design for Efficient Neuron Reconstruction Software Based on the SWC Format.

Authors:  Linqing Feng; Ting Zhao; Jinhyun Kim
Journal:  eNeuro       Date:  2015-01-02

9.  V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets.

Authors:  Hanchuan Peng; Zongcai Ruan; Fuhui Long; Julie H Simpson; Eugene W Myers
Journal:  Nat Biotechnol       Date:  2010-03-14       Impact factor: 54.908

10.  High-throughput dual-colour precision imaging for brain-wide connectome with cytoarchitectonic landmarks at the cellular level.

Authors:  Hui Gong; Dongli Xu; Jing Yuan; Xiangning Li; Congdi Guo; Jie Peng; Yuxin Li; Lindsay A Schwarz; Anan Li; Bihe Hu; Benyi Xiong; Qingtao Sun; Yalun Zhang; Jiepeng Liu; Qiuyuan Zhong; Tonghui Xu; Shaoqun Zeng; Qingming Luo
Journal:  Nat Commun       Date:  2016-07-04       Impact factor: 14.919

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