Literature DB >> 21399937

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

Yu Wang1, Arunachalam Narayanaswamy, Chia-Ling Tsai, Badrinath Roysam.   

Abstract

This paper presents a broadly applicable algorithm and a comprehensive open-source software implementation for automated tracing of neuronal structures in 3-D microscopy images. The core 3-D neuron tracing algorithm is based on three-dimensional (3-D) open-curve active Contour (Snake). It is initiated from a set of automatically detected seed points. Its evolution is driven by a combination of deforming forces based on the Gradient Vector Flow (GVF), stretching forces based on estimation of the fiber orientations, and a set of control rules. In this tracing model, bifurcation points are detected implicitly as points where multiple snakes collide. A boundariness measure is employed to allow local radius estimation. A suite of pre-processing algorithms enable the system to accommodate diverse neuronal image datasets by reducing them to a common image format. The above algorithms form the basis for a comprehensive, scalable, and efficient software system developed for confocal or brightfield images. It provides multiple automated tracing modes. The user can optionally interact with the tracing system using multiple view visualization, and exercise full control to ensure a high quality reconstruction. We illustrate the utility of this tracing system by presenting results from a synthetic dataset, a brightfield dataset and two confocal datasets from the DIADEM challenge.

Mesh:

Year:  2011        PMID: 21399937     DOI: 10.1007/s12021-011-9110-5

Source DB:  PubMed          Journal:  Neuroinformatics        ISSN: 1539-2791


  27 in total

1.  Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction.

Authors:  Stephen R Aylward; Elizabeth Bullitt
Journal:  IEEE Trans Med Imaging       Date:  2002-02       Impact factor: 10.048

2.  Automatic neuron tracing in volumetric microscopy images with anisotropic path searching.

Authors:  Jun Xie; Ting Zhao; Tzumin Lee; Eugene Myers; Hanchuan Peng
Journal:  Med Image Comput Comput Assist Interv       Date:  2010

3.  Repulsive force based snake model to segment and track neuronal axons in 3D microscopy image stacks.

Authors:  Hongmin Cai; Xiaoyin Xu; Ju Lu; Jeff W Lichtman; S P Yung; Stephen T C Wong
Journal:  Neuroimage       Date:  2006-07-24       Impact factor: 6.556

4.  NeuriteTracer: a novel ImageJ plugin for automated quantification of neurite outgrowth.

Authors:  Madeline Pool; Joachim Thiemann; Amit Bar-Or; Alyson E Fournier
Journal:  J Neurosci Methods       Date:  2007-09-08       Impact factor: 2.390

5.  Snakes, shapes, and gradient vector flow.

Authors:  C Xu; J L Prince
Journal:  IEEE Trans Image Process       Date:  1998       Impact factor: 10.856

6.  Using nonlinear diffusion and mean shift to detect and connect cross-sections of axons in 3D optical microscopy images.

Authors:  Hongmin Cai; Xiaoyin Xu; Ju Lu; Jeff Lichtman; S P Yung; Stephen T C Wong
Journal:  Med Image Anal       Date:  2008-03-25       Impact factor: 8.545

7.  New techniques for imaging, digitization and analysis of three-dimensional neural morphology on multiple scales.

Authors:  S L Wearne; A Rodriguez; D B Ehlenberger; A B Rocher; S C Henderson; P R Hof
Journal:  Neuroscience       Date:  2005       Impact factor: 3.590

8.  Robust adaptive 3-D segmentation of vessel laminae from fluorescence confocal microscope images and parallel GPU implementation.

Authors:  Arunachalam Narayanaswamy; Saritha Dwarakapuram; Christopher S Bjornsson; Barbara M Cutler; William Shain; Badrinath Roysam
Journal:  IEEE Trans Med Imaging       Date:  2010-03       Impact factor: 10.048

9.  MDL constrained 3-D grayscale skeletonization algorithm for automated extraction of dendrites and spines from fluorescence confocal images.

Authors:  Xiaosong Yuan; Joshua T Trachtenberg; Steve M Potter; Badrinath Roysam
Journal:  Neuroinformatics       Date:  2009-12-11

10.  Reconstruction of the neuromuscular junction connectome.

Authors:  Ranga Srinivasan; Qing Li; Xiaobo Zhou; Ju Lu; Jeff Lichtman; Stephen T C Wong
Journal:  Bioinformatics       Date:  2010-06-15       Impact factor: 6.937

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  63 in total

1.  TReMAP: Automatic 3D Neuron Reconstruction Based on Tracing, Reverse Mapping and Assembling of 2D Projections.

Authors:  Zhi Zhou; Xiaoxiao Liu; Brian Long; Hanchuan Peng
Journal:  Neuroinformatics       Date:  2016-01

2.  NeuroGPS-Tree: automatic reconstruction of large-scale neuronal populations with dense neurites.

Authors:  Tingwei Quan; Hang Zhou; Jing Li; Shiwei Li; Anan Li; Yuxin Li; Xiaohua Lv; Qingming Luo; Hui Gong; Shaoqun Zeng
Journal:  Nat Methods       Date:  2015-11-23       Impact factor: 28.547

3.  3-D image pre-processing algorithms for improved automated tracing of neuronal arbors.

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

Review 4.  Neuronal tracing for connectomic studies.

Authors:  Ju Lu
Journal:  Neuroinformatics       Date:  2011-09

5.  From DIADEM to BigNeuron.

Authors:  Hanchuan Peng; Erik Meijering; Giorgio A Ascoli
Journal:  Neuroinformatics       Date:  2015-07

6.  BlastNeuron for Automated Comparison, Retrieval and Clustering of 3D Neuron Morphologies.

Authors:  Yinan Wan; Fuhui Long; Lei Qu; Hang Xiao; Michael Hawrylycz; Eugene W Myers; Hanchuan Peng
Journal:  Neuroinformatics       Date:  2015-10

7.  From Curves to Trees: A Tree-like Shapes Distance Using the Elastic Shape Analysis Framework.

Authors:  A Mottini; X Descombes; F Besse
Journal:  Neuroinformatics       Date:  2015-04

8.  Automatic Morphological Reconstruction of Neurons from Multiphoton and Confocal Microscopy Images Using 3D Tubular Models.

Authors:  Alberto Santamaría-Pang; Paul Hernandez-Herrera; Manos Papadakis; Peter Saggau; Ioannis A Kakadiaris
Journal:  Neuroinformatics       Date:  2015-07

9.  Brain-Wide Shape Reconstruction of a Traced Neuron Using the Convex Image Segmentation Method.

Authors:  Shiwei Li; Tingwei Quan; Hang Zhou; Qing Huang; Tao Guan; Yijun Chen; Cheng Xu; Hongtao Kang; Anan Li; Ling Fu; Qingming Luo; Hui Gong; Shaoqun Zeng
Journal:  Neuroinformatics       Date:  2020-04

Review 10.  Neuronal morphology goes digital: a research hub for cellular and system neuroscience.

Authors:  Ruchi Parekh; Giorgio A Ascoli
Journal:  Neuron       Date:  2013-03-20       Impact factor: 17.173

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