Clustering of whole brain white matter short association bundles using HARDI data

HomeAccepted Journals, FONDECYT 1161427 - Publications, Publication

Clustering of whole brain white matter short association bundles using HARDI data

C. Román, M. Guevara, R. Valenzuela, M. Figueroa, J. Houenou, D. Duclap, C. Poupon, J.-F. Mangin, P. Guevara. Clustering of whole brain white matter short association bundles using HARDI data. Frontiers in Neuroinformatics, 11:73, 2017.

DOI: https://doi.org/10.3389/fninf.2017.00073

By Pamela Guevara| 2019-03-18T03:25:53-03:00 December 22nd, 2017|Accepted Journals, FONDECYT 1161427 - Publications, Publication|0 Comments

About the Author: Pamela Guevara

Enhanced Automatic Segmentation for Superficial White Matter Fiber Bundles for Probabilistic Tractography Datasets
Enhanced Automatic Segmentation for Superficial White Matter Fiber Bundles for Probabilistic Tractography Datasets
Group-Wise Cortical Surface Parcellation Based on Inter-Subject Fiber Clustering
Group-Wise Cortical Surface Parcellation Based on Inter-Subject Fiber Clustering
Machine learning to investigate superficial white matter integrity in early multiple sclerosis
Machine learning to investigate superficial white matter integrity in early multiple sclerosis
Fiber Clustering Acceleration With a Modified Kmeans++ Algorithm Using Data Parallelism
Fiber Clustering Acceleration With a Modified Kmeans++ Algorithm Using Data Parallelism
Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?
Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

Clustering of whole brain white matter short association bundles using HARDI data

Clustering of whole brain white matter short association bundles using HARDI data

Share This Story, Choose Your Platform!

About the Author: Pamela Guevara

Related Posts

Enhanced Automatic Segmentation for Superficial White Matter Fiber Bundles for Probabilistic Tractography Datasets

Group-Wise Cortical Surface Parcellation Based on Inter-Subject Fiber Clustering

Machine learning to investigate superficial white matter integrity in early multiple sclerosis

Fiber Clustering Acceleration With a Modified Kmeans++ Algorithm Using Data Parallelism

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

Leave A Comment Cancel reply