Clustering of tractography datasets based on streamline point distribution

HomeConferencias Internacionales, FONDECYT 1161427 - Publicaciones, Publicación

Clustering of tractography datasets based on streamline point distribution

A. Sánchez, C. Hernández, C. Poupon, J.-F. Mangin, P. Guevara. Clustering of tractography datasets based on streamline point distribution. In International Society of Magnetic Resonance in Medicine conference, ISMRM 2018, Paris, France, 2018.

http://cds.ismrm.org/protected/18MPresentations/abstracts/1567.html

By Pamela Guevara| 2018-08-29T14:08:37-03:00 Marzo 16th, 2018|Conferencias Internacionales, FONDECYT 1161427 - Publicaciones, Publicación|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?

L	Ma	Mi	J	V	S	D
1	2	3	4	5	6	7
8	9	10	11	12	13	14
15	16	17	18	19	20	21
22	23	24	25	26	27	28
29	30	31

Clustering of tractography datasets based on streamline point distribution

Clustering of tractography datasets based on streamline point distribution

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 Cancelar respuesta