Treffer: GPU tractography: What can we learn from half a trillion streamlines?

Title:
GPU tractography: What can we learn from half a trillion streamlines?
Authors:
Aeschlimann, Yanis, Deslauriers-Gauthier, Samuel, Veltz, Romain
Contributors:
Aeschlimann, Yanis
Publisher Information:
2025.
Publication Year:
2025
Subject Terms:
Structural connectome, [SCCO.COMP] Cognitive science/Computer science, Gpu acceleration, [SCCO.NEUR] Cognitive science/Neuroscience, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, Uncertainties evaluation, Diffusion tractography imaging, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
Document Type:
Konferenz Conference object
File Description:
application/pdf
Language:
English
Access URL:
https://inria.hal.science/hal-05272265v1
Rights:
CC BY
Accession Number:
edsair.dedup.wf.002..3d1a56a8f0696f0df9c0d7a1b2c7081c
Database:
OpenAIRE

Weitere Informationen

Using 500,000,000,000 seeds, we compute tight bounds on the variance of the connection probability and show that the recommended approach has high uncertainty.