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Osorio I, Guevara M, Bonometti D, et al. ABrainVis: an android brain image visualization tool. Biomed Eng Online. 2021;20(1):72doi: 10.1186/s12938-021-00909-0.
Osorio, I., Guevara, M., Bonometti, D., Carrasco, D., Descoteaux, M., Poupon, C., Mangin, J. F., Hernández, C., & Guevara, P. (2021). ABrainVis: an android brain image visualization tool. Biomedical engineering online, 20(1), 72. https://doi.org/10.1186/s12938-021-00909-0
Osorio, Ignacio, et al. "ABrainVis: an android brain image visualization tool." Biomedical engineering online vol. 20,1 (2021): 72. doi: https://doi.org/10.1186/s12938-021-00909-0
Osorio I, Guevara M, Bonometti D, Carrasco D, Descoteaux M, Poupon C, Mangin JF, Hernández C, Guevara P. ABrainVis: an android brain image visualization tool. Biomed Eng Online. 2021 Jul 29;20(1):72. doi: 10.1186/s12938-021-00909-0. PMID: 34325693; PMCID: PMC8323223.
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Biomed Eng Online. 2021 Jul 29;20(1):72. doi: 10.1186/s12938-021-00909-0.

ABrainVis: an android brain image visualization tool.

Biomedical engineering online

Ignacio Osorio, Miguel Guevara, Danilo Bonometti, Diego Carrasco, Maxime Descoteaux, Cyril Poupon, Jean-François Mangin, Cecilia Hernández, Pamela Guevara

Affiliations

  1. Department of Computer Sciences, Universidad de Concepción, Concepción, Chile.
  2. Université Paris-Saclay, CEA, CNRS, Neurospin, BAOBAB, Gif-sur-Yvette, France.
  3. Department of Electrical Engineering, Universidad de Concepción, Concepción, Chile.
  4. Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, Canada.
  5. Center for Biotechnology and Bioengineering (CeBiB), Santiago, Chile.
  6. Department of Electrical Engineering, Universidad de Concepción, Concepción, Chile. [email protected].

PMID: 34325693 PMCID: PMC8323223 DOI: 10.1186/s12938-021-00909-0

Abstract

BACKGROUND: The visualization and analysis of brain data such as white matter diffusion tractography and magnetic resonance imaging (MRI) volumes is commonly used by neuro-specialist and researchers to help the understanding of brain structure, functionality and connectivity. As mobile devices are widely used among users and their technology shows a continuous improvement in performance, different types of applications have been designed to help users in different work areas.

RESULTS: We present, ABrainVis, an Android mobile tool that allows users to visualize different types of brain images, such as white matter diffusion tractographies, represented as fibers in 3D, segmented fiber bundles, MRI 3D images as rendered volumes and slices, and meshes. The tool enables users to choose and combine different types of brain imaging data to provide visual anatomical context for specific visualization needs. ABrainVis provides high performance over a wide range of Android devices, including tablets and cell phones using medium and large tractography datasets. Interesting visualizations including brain tumors and arteries, along with fiber, are given as examples of case studies using ABrainVis.

CONCLUSIONS: The functionality, flexibility and performance of ABrainVis tool introduce an improvement in user experience enabling neurophysicians and neuroscientists fast visualization of large tractography datasets, as well as the ability to incorporate other brain imaging data such as MRI volumes and meshes, adding anatomical contextual information.

© 2021. The Author(s).

Keywords: 3D rendering; Brain imaging; Mobile visualization

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