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Title:

Visualizing anatomically registered data with brainrender.

Document type:
Article; Evaluation Study; Journal Article; Research Support, Non-U.S. Gov't
Author(s):
Claudi, Federico; Tyson, Adam L; Petrucco, Luigi; Margrie, Troy W; Portugues, Ruben; Branco, Tiago
Abstract:
Three-dimensional (3D) digital brain atlases and high-throughput brain-wide imaging techniques generate large multidimensional datasets that can be registered to a common reference frame. Generating insights from such datasets depends critically on visualization and interactive data exploration, but this a challenging task. Currently available software is dedicated to single atlases, model species or data types, and generating 3D renderings that merge anatomically registered data from diverse so...     »
Journal title abbreviation:
Elife
Year:
2021
Journal volume:
10
Fulltext / DOI:
doi:10.7554/eLife.65751
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/33739286
TUM Institution:
Institut für Neurowissenschaften
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