Literature DB >> 8321013

A system for quantitative morphological measurement and electronic modelling of neurons: three-dimensional reconstruction.

E W Stockley1, H M Cole, A D Brown, H V Wheal.   

Abstract

A system for accurately reconstructing neurones from optical sections taken at high magnification is described. Cells are digitised on a 68000-based microcomputer to form a database consisting of a series of linked nodes each consisting of x, y, z coordinates and an estimate of dendritic diameter. This database is used to generate three-dimensional (3-D) displays of the neurone and allows quantitative analysis of the cell volume, surface area and dendritic length. Images of the cell can be manipulated locally or transferred to an IBM 3090 mainframe where a wireframe model can be displayed on an IBM 5080 graphics terminal and rotated interactively in real time, allowing visualisation of the cell from all angles. Space-filling models can also be produced. Reconstructions can also provide morphological data for passive electrical simulations of hippocampal pyramidal cells.

Mesh:

Year:  1993        PMID: 8321013     DOI: 10.1016/0165-0270(93)90020-r

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  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.  Volumes of chick and rat osteoclasts cultured on glass.

Authors:  K Piper; A Boyde; S J Jones
Journal:  Calcif Tissue Int       Date:  1995-05       Impact factor: 4.333

3.  Quantifying How Staining Methods Bias Measurements of Neuron Morphologies.

Authors:  Roozbeh Farhoodi; Benjamin James Lansdell; Konrad Paul Kording
Journal:  Front Neuroinform       Date:  2019-05-21       Impact factor: 4.081

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

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

5.  Neuron type classification in rat brain based on integrative convolutional and tree-based recurrent neural networks.

Authors:  Tielin Zhang; Yi Zeng; Yue Zhang; Xinhe Zhang; Mengting Shi; Likai Tang; Duzhen Zhang; Bo Xu
Journal:  Sci Rep       Date:  2021-03-31       Impact factor: 4.379

6.  A tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypes.

Authors:  Gloria Colombo; Ryan John A Cubero; Lida Kanari; Alessandro Venturino; Rouven Schulz; Martina Scolamiero; Jens Agerberg; Hansruedi Mathys; Li-Huei Tsai; Wojciech Chachólski; Kathryn Hess; Sandra Siegert
Journal:  Nat Neurosci       Date:  2022-09-30       Impact factor: 28.771

Review 7.  Analysis Tools for Large Connectomes.

Authors:  Louis K Scheffer
Journal:  Front Neural Circuits       Date:  2018-10-15       Impact factor: 3.492

8.  Module for SWC neuron morphology file validation and correction enabled for high throughput batch processing.

Authors:  Damien M O'Halloran
Journal:  PLoS One       Date:  2020-01-23       Impact factor: 3.240

  8 in total

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