Parallel Optimization of Fiber Bundle Segmentation for Massive Tractography Datasets

@article{Vzquez2019ParallelOO,
  title={Parallel Optimization of Fiber Bundle Segmentation for Massive Tractography Datasets},
  author={Andrea V{\'a}zquez and Narciso L{\'o}pez-L{\'o}pez and Nicole Labra and Miguel Figueroa and Cyril Poupon and Jean-Francois Mangin and Cecilia Hern{\'a}ndez and Pamela Guevara},
  journal={2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)},
  year={2019},
  pages={178-181}
}
  • Andrea Vázquez, Narciso López-López, +5 authors Pamela Guevara
  • Published in
    IEEE 16th International…
    2019
  • Computer Science, Engineering, Biology
  • We present an optimized algorithm that performs automatic classification of white matter fibers based on a multi-subject bundle atlas. We implemented a parallel algorithm that improves upon its previous version in both execution time and memory usage. Our new version uses the local memory of each processor, which leads to a reduction in execution time. Hence, it allows the analysis of bigger subject and/or atlas datasets. As a result, the segmentation of a subject of 4,145,000 fibers is reduced… CONTINUE READING

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