NeuroTessMesh: a tool for the generation and visualization of neuron meshes and adaptive on-the-fly refinement

García-Cantero, Juan and Brito Méndez, Juan Pedro and Mata Fernández, Susana and Bayona Beriso, Sofía and Pastor Pérez, Luis (2017). NeuroTessMesh: a tool for the generation and visualization of neuron meshes and adaptive on-the-fly refinement. "Frontiers in Neuroinformatics", v. 11 ; pp. 1-14. ISSN 1662-5196. https://doi.org/10.3389/fninf.2017.00038.

Description

Title: NeuroTessMesh: a tool for the generation and visualization of neuron meshes and adaptive on-the-fly refinement
Author/s:
  • García-Cantero, Juan
  • Brito Méndez, Juan Pedro
  • Mata Fernández, Susana
  • Bayona Beriso, Sofía
  • Pastor Pérez, Luis
Item Type: Article
Título de Revista/Publicación: Frontiers in Neuroinformatics
Date: June 2017
ISSN: 1662-5196
Volume: 11
Subjects:
Freetext Keywords: Geometry-based techniques; Multiresolution techniques; GPUs and multi-core architectures; Compression techniques; Bioinformatics visualization
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Arquitectura y Tecnología de Sistemas Informáticos
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (3MB) | Preview

Abstract

Gaining a better understanding of the human brain continues to be one of the greatest challenges for science, largely because of the overwhelming complexity of the brain and the difficulty of analyzing the features and behavior of dense neural networks. Regarding analysis, 3D visualization has proven to be a useful tool for the evaluation of complex systems. However, the large number of neurons in non-trivial circuits, together with their intricate geometry, makes the visualization of a neuronal scenario an extremely challenging computational problem. Previous work in this area dealt with the generation of 3D polygonal meshes that approximated the cells’ overall anatomy but did not attempt to deal with the extremely high storage and computational cost required to manage a complex scene. This paper presents NeuroTessMesh, a tool specifically designed to cope with many of the problems associated with the visualization of neural circuits that are comprised of large numbers of cells. In addition, this method facilitates the recovery and visualization of the 3D geometry of cells included in databases, such as NeuroMorpho, and provides the tools needed to approximate missing information such as the soma’s morphology. This method takes as its only input the available compact, yet incomplete, morphological tracings of the cells as acquired by neuroscientists. It uses a multiresolution approach that combines an initial, coarse mesh generation with subsequent on-the-fly adaptive mesh refinement stages using tessellation shaders. For the coarse mesh generation, a novel approach, based on the Finite Element Method, allows approximation of the 3D shape of the soma from its incomplete description. Subsequently, the adaptive refinement process performed in the graphic card generates meshes that provide good visual quality geometries at a reasonable computational cost, both in terms of memory and rendering time. All the described techniques have been integrated into NeuroTessMesh, available to the scientific community, to generate, visualize, and save the adaptive resolution meshes.

Funding Projects

TypeCodeAcronymLeaderTitle
Horizon 2020720270HBP SGA1UnspecifiedHuman Brain Project Specific Grant Agreement 1
Government of SpainC080020-09UnspecifiedUnspecifiedUnspecified
Government of SpainTIN2014-57481NAVANUnspecifiedUnspecified

More information

Item ID: 50774
DC Identifier: http://oa.upm.es/50774/
OAI Identifier: oai:oa.upm.es:50774
DOI: 10.3389/fninf.2017.00038
Official URL: https://www.frontiersin.org/articles/10.3389/fninf.2017.00038/full
Deposited by: Memoria Investigacion
Deposited on: 16 May 2018 09:50
Last Modified: 02 Apr 2019 06:53
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM