Development and optimization of tools for the study of human brain anatomical connectivity using high angular resolution diffusion MRI

Project Type: FONDECYT Initiation #11121644
Position: Principal Researcher
Award Year: 2012. Ending Year: 2015.

Descripción

This project sought to develop and optimize tools for the study and analysis of brain connectivity, using Difussion Magnetic Resonance Imaging (dMRI) data.

The studies are based on High Angular Resolution Difussion Imaging (HARDI) images.

These present very high quality, due to the advancement of acquisition technologies, as well as the acquisition itself (long duration, dedicated to research) and the performed post-processing, which seek to provide a solid base for the study of the healthy adult human brain.

The main results of this project contemplate:

  • The analysis of the reproducibility of short association fascicles of the brain, using data clustering tools and cortical parcellations.

  • The optimization of an algorithm for the segmentation of brain fibers, achieving times that allow an interactive segmentation (Principal Researcher: Professor Miguel Figueroa T.).

  • The development of a tool for the optimized visualization and manipulation of brain tracts.

Other interesting results are:

  • Development of a tool for the optimized visualization of tracts for Android devices (iFiber).

  • Creation of an atlas of short brain fascicles.

  • Development of algorithms for the comparison of brain tracts, between subjects and between hemispheres.

Undergraduate Theses related to the project

Student Thesis Defense Date
Ignacio Osorio W. Electronic Civil Engineering Thesis: “Software for the Interactive Visualization and Extraction of Brain Fibers” December 31st, 2015.
Danilo Bonometti B. Electronic Civil Engineering Thesis: “Visualization of Brain Fibers” April 1st, 2015.
Daniel Seguel B. Biomedical Civil Engineering Thesis: “Automatic Algorithm for the Segmentation of Short Association Fibers of the Human Brain” March 17th, 2015.
Claudio Román G. Biomedical Civil Engineering Thesis: “Short Brain Fibers Clustering Calculated from Difussion Magnetic Resonance Imaging Images” January 16th, 2015.
Miguel Guevara O. Biomedical Civil Engineering Thesis: “Algorithm for the Automatic Segmentation of Short Brain Fibers of the Fronto-Parietal Region and the Insular Cortex” January 16th, 2015.
Pablo L. Silva P. Biomedical Civil Engineering Thesis: “Parcellation of the Brain Cortex Based on the Anatomical Connectivity” May 29th, 2014.
Eduardo Venegas A. Electronic Civil Engineering Thesis: “Development of a software for the interactive manipulation of brain fibers” July 18th, 2014.
Nicole A. Labra A. Biomedical Civil Engineering Thesis: “Optimization of Algorithm for the Classification of White Matter Fibers based on the Brain Fascicles Atlas” April 30th, 2013.
Edison Pardo R. Electronic Civil Engineering Thesis: “Study of the Variability of the Connections of Short Association of the Human Brain” April 4th, 2013.
Gabriel E. Varela M. Biomedical Civil Engineering Thesis: “Calculation of Diffusion Tensor Indices from the Westin Algorithm” April 4th, 2013.

Postgraduate Theses related to the project

Student Thesis Defense Date
Claudio Román G. Master of Engineering Sciences w/m in Electrical Engineering.
“Segmentation of brain short brain fibers based on hierarchical Clustering from HARDI database”
November 30th, 2016.
Miguel Guevara O. Master of Engineering Sciences w/m in Electrical Engineering.
“Parcellation of the brain cortex based on fiber atlas calculated from tractography”
January 30th, 2016.
Nicole Labra A. Master of Engineering Sciences w/m in Electrical Engineering, (co-director)
“Quick segmentation of white substance brain fibers”
January 28th, 2015.

Publications

502, 2025

FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare.

K. Lekadir, AF. Frangi, AR. Porras, B. Glocker, C. Cintas, CP. Langlotz, E. Weicken, FW. Asselbergs, F. Prior, GS. Collins, G. Kaissis, G. Tsakou, I. Buvat, J. Kalpathy-Cramer, J. Mongan, JA. Schnabel, K. Kushibar, K. Riklund, K. Marias, LM. Amugongo, LA. Fromont, L. Maier-Hein, L. Cerdá-Alberich, L. Martí-Bonmatí, MJ. Cardoso, M. Bobowicz, M. Shabani, M. Tsiknakis, MA. Zuluaga, MC. Fritzsche, M. Camacho, MG. Linguraru, M. Wenzel, M. De Bruijne, MG. Tolsgaard, M. Goisauf, M. Cano Abadía, N. Papanikolaou, N. Lazrak, O. Pujol, R. Osuala, S. Napel, S. Colantonio, S. Joshi, S. Klein, S. Aussó, WA. Rogers, Z. Salahuddin, MPA. Starmans, FUTURE-AI Consortium. FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare. BMJ, Volume 388, Febraury 5th, 2025, e081554. DOI: https://doi.org/10.1136/bmj-2024-081554

1708, 2024

Patients recovering from COVID-19 who presented with anosmia during their acute episode have behavioral, functional, and structural brain alterations.

L. Kausel, A. Figueroa-Vargas, F. Zamorano, X. Stecher, M. Aspé-Sánchez, P. Carvajal-Paredes, V. Márquez-Rodríguez, MP. Martínez-Molina, C. Román, P. Soto-Fernández, G. Valdebenito-Oyarzo, C. Manterola, R. Uribe-San-Martín, C. Silva, R. Henríquez-Ch, F. Aboitiz, R. Polania, P. Guevara, P. Muñoz-Venturelli, P. Soto-Icaza, P. Billeke. Patients recovering from COVID-19 who presented with anosmia during their acute episode have behavioral, functional, and structural brain alterations. Scientific Reports, Volume 14, August 17th, 2024, 19049. DOI: https://doi.org/10.1038/s41598-024-69772-y

News

2018-11-10T18:32:47-03:00

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