Literature DB >> 19834225

An interactive visualization tool for multi-channel confocal microscopy data in neurobiology research.

Yong Wan1, Hideo Otsuna, Chi-Bin Chien, Charles Hansen.   

Abstract

Confocal microscopy is widely used in neurobiology for studying the three-dimensional structure of the nervous system. Confocal image data are often multi-channel, with each channel resulting from a different fluorescent dye or fluorescent protein; one channel may have dense data, while another has sparse; and there are often structures at several spatial scales: subneuronal domains, neurons, and large groups of neurons (brain regions). Even qualitative analysis can therefore require visualization using techniques and parameters fine-tuned to a particular dataset. Despite the plethora of volume rendering techniques that have been available for many years, the techniques standardly used in neurobiological research are somewhat rudimentary, such as looking at image slices or maximal intensity projections. Thus there is a real demand from neurobiologists, and biologists in general, for a flexible visualization tool that allows interactive visualization of multi-channel confocal data, with rapid fine-tuning of parameters to reveal the three-dimensional relationships of structures of interest. Together with neurobiologists, we have designed such a tool, choosing visualization methods to suit the characteristics of confocal data and a typical biologist's workflow. We use interactive volume rendering with intuitive settings for multidimensional transfer functions, multiple render modes and multi-views for multi-channel volume data, and embedding of polygon data into volume data for rendering and editing. As an example, we apply this tool to visualize confocal microscopy datasets of the developing zebrafish visual system.

Entities:  

Mesh:

Year:  2009        PMID: 19834225      PMCID: PMC2874972          DOI: 10.1109/TVCG.2009.118

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  6 in total

1.  Systematic analysis of the visual projection neurons of Drosophila melanogaster. I. Lobula-specific pathways.

Authors:  Hideo Otsuna; Kei Ito
Journal:  J Comp Neurol       Date:  2006-08-20       Impact factor: 3.215

2.  High-level user interfaces for transfer function design with semantics.

Authors:  Christof Rezk Salama; Maik Keller; Peter Kohlmann
Journal:  IEEE Trans Vis Comput Graph       Date:  2006 Sep-Oct       Impact factor: 4.579

3.  Genetic single-cell mosaic analysis implicates ephrinB2 reverse signaling in projections from the posterior tectum to the hindbrain in zebrafish.

Authors:  Tomomi Sato; Takanori Hamaoka; Hidenori Aizawa; Toshihiko Hosoya; Hitoshi Okamoto
Journal:  J Neurosci       Date:  2007-05-16       Impact factor: 6.167

4.  Reconstruction of cellular biological structures from optical microscopy data.

Authors:  Kishore Mosaliganti; Lee Cooper; Richard Sharp; Raghu Machiraju; Gustavo Leone; Kun Huang; Joel Saltz
Journal:  IEEE Trans Vis Comput Graph       Date:  2008 Jul-Aug       Impact factor: 4.579

5.  Perception of surface curvature and direction of illumination from patterns of shading.

Authors:  J T Todd; E Mingolla
Journal:  J Exp Psychol Hum Percept Perform       Date:  1983-08       Impact factor: 3.332

6.  Laterotopic representation of left-right information onto the dorso-ventral axis of a zebrafish midbrain target nucleus.

Authors:  Hidenori Aizawa; Isaac H Bianco; Takanori Hamaoka; Toshio Miyashita; Osamu Uemura; Miguel L Concha; Claire Russell; Stephen W Wilson; Hitoshi Okamoto
Journal:  Curr Biol       Date:  2005-02-08       Impact factor: 10.834

  6 in total
  48 in total

1.  nev (cyfip2) is required for retinal lamination and axon guidance in the zebrafish retinotectal system.

Authors:  Andrew J Pittman; John A Gaynes; Chi-Bin Chien
Journal:  Dev Biol       Date:  2010-06-09       Impact factor: 3.582

2.  Matching visual saliency to confidence in plots of uncertain data.

Authors:  David Feng; Lester Kwock; Yueh Lee; Russell M Taylor
Journal:  IEEE Trans Vis Comput Graph       Date:  2010 Nov-Dec       Impact factor: 4.579

3.  Burst generation mediated by cholinergic input in terminal nerve-gonadotrophin releasing hormone neurones of the goldfish.

Authors:  Takafumi Kawai; Hideki Abe; Yoshitaka Oka
Journal:  J Physiol       Date:  2013-08-19       Impact factor: 5.182

4.  Neuroarchitecture and neuroanatomy of the Drosophila central complex: A GAL4-based dissection of protocerebral bridge neurons and circuits.

Authors:  Tanya Wolff; Nirmala A Iyer; Gerald M Rubin
Journal:  J Comp Neurol       Date:  2014-12-16       Impact factor: 3.215

5.  FluoRender: An Application of 2D Image Space Methods for 3D and 4D Confocal Microscopy Data Visualization in Neurobiology Research.

Authors:  Yong Wan; Hideo Otsuna; Chi-Bin Chien; Charles Hansen
Journal:  IEEE Pac Vis Symp       Date:  2012

6.  Visualization of Neuronal Structures in Wide-Field Microscopy Brain Images.

Authors:  Saeed Boorboor; Mala Ananth; David Talmage; Arie Kaufman
Journal:  IEEE Trans Vis Comput Graph       Date:  2018-08-20       Impact factor: 4.579

7.  Wiring patterns from auditory sensory neurons to the escape and song-relay pathways in fruit flies.

Authors:  Hyunsoo Kim; Mihoko Horigome; Yuki Ishikawa; Feng Li; J Scott Lauritzen; Gwyneth Card; Davi D Bock; Azusa Kamikouchi
Journal:  J Comp Neurol       Date:  2020-02-19       Impact factor: 3.215

8.  ConnectomeExplorer: query-guided visual analysis of large volumetric neuroscience data.

Authors:  Johanna Beyer; Ali Al-Awami; Narayanan Kasthuri; Jeff W Lichtman; Hanspeter Pfister; Markus Hadwiger
Journal:  IEEE Trans Vis Comput Graph       Date:  2013-12       Impact factor: 4.579

9.  Internal amino acid state modulates yeast taste neurons to support protein homeostasis in Drosophila.

Authors:  Kathrin Steck; Samuel J Walker; Pavel M Itskov; Célia Baltazar; José-Maria Moreira; Carlos Ribeiro
Journal:  Elife       Date:  2018-02-02       Impact factor: 8.140

10.  Interactive Extraction of Neural Structures with User-Guided Morphological Diffusion.

Authors:  Yong Wan; Hideo Otsuna; Chi-Bin Chien; Charles Hansen
Journal:  Proc IEEE Symp Biol Data Vis       Date:  2012
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