Literature DB >> 28065895

Automated neuron tracing using probability hypothesis density filtering.

Miroslav Radojevic, Erik Meijering.   

Abstract

Motivation: The functionality of neurons and their role in neuronal networks is tightly connected to the cell morphology. A fundamental problem in many neurobiological studies aiming to unravel this connection is the digital reconstruction of neuronal cell morphology from microscopic image data. Many methods have been developed for this, but they are far from perfect, and better methods are needed.
Results: Here we present a new method for tracing neuron centerlines needed for full reconstruction. The method uses a fundamentally different approach than previous methods by considering neuron tracing as a Bayesian multi-object tracking problem. The problem is solved using probability hypothesis density filtering. Results of experiments on 2D and 3D fluorescence microscopy image datasets of real neurons indicate the proposed method performs comparably or even better than the state of the art. Availability and Implementation: Software implementing the proposed neuron tracing method was written in the Java programming language as a plugin for the ImageJ platform. Source code is freely available for non-commercial use at https://bitbucket.org/miroslavradojevic/phd . Contact: meijering@imagescience.org. Supplementary information: Supplementary data are available at Bioinformatics online.
© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Mesh:

Year:  2017        PMID: 28065895     DOI: 10.1093/bioinformatics/btw751

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  8 in total

1.  TraceMontage: A method for merging multiple independent neuronal traces.

Authors:  Aslan S Dizaji; Logan A Walker; Dawen Cai
Journal:  J Neurosci Methods       Date:  2019-12-24       Impact factor: 2.390

2.  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

3.  Super-resolution Segmentation Network for Reconstruction of Packed Neurites.

Authors:  Hang Zhou; Tingting Cao; Tian Liu; Shijie Liu; Lu Chen; Yijun Chen; Qing Huang; Wei Ye; Shaoqun Zeng; Tingwei Quan
Journal:  Neuroinformatics       Date:  2022-07-19

4.  Hidden Markov modeling for maximum probability neuron reconstruction.

Authors:  Thomas L Athey; Daniel J Tward; Ulrich Mueller; Joshua T Vogelstein; Michael I Miller
Journal:  Commun Biol       Date:  2022-04-25

5.  Automated Neuron Reconstruction from 3D Fluorescence Microscopy Images Using Sequential Monte Carlo Estimation.

Authors:  Miroslav Radojević; Erik Meijering
Journal:  Neuroinformatics       Date:  2019-07

6.  Random-Reaction-Seed Method for Automated Identification of Neurite Elongation and Branching.

Authors:  Alvason Zhenhua Li; Lawrence Corey; Jia Zhu
Journal:  Sci Rep       Date:  2019-02-27       Impact factor: 4.379

7.  Optimization of Traced Neuron Skeleton Using Lasso-Based Model.

Authors:  Shiwei Li; Tingwei Quan; Cheng Xu; Qing Huang; Hongtao Kang; Yijun Chen; Anan Li; Ling Fu; Qingming Luo; Hui Gong; Shaoqun Zeng
Journal:  Front Neuroanat       Date:  2019-02-21       Impact factor: 3.856

8.  Identifying Weak Signals in Inhomogeneous Neuronal Images for Large-Scale Tracing of Sparsely Distributed Neurites.

Authors:  Shiwei Li; Tingwei Quan; Hang Zhou; FangFang Yin; Anan Li; Ling Fu; Qingming Luo; Hui Gong; Shaoqun Zeng
Journal:  Neuroinformatics       Date:  2019-10
  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.