Abstract #2588
Il Gatto Sta Ingrassando: Novel Connectivity Tools and Additions in AFNI-FATCAT
Paul A Taylor 1,2 and Ziad S Saad 3
1
Faculty of Health Sciences, University of
Cape Town, Cape Town, Western Cape, South Africa,
2
African
Institute for Mathematical Sciences, South Africa,
3
NIMH,
National Institutes of Health, Bethesda, MD, United
States
We present developments in the AFNI-FATCAT suit of tools
for analyzing MRI functional and structural
connectivity. Improvements include: enhanced
deterministic tracking to utilize voxelwise uncertainty;
increased options for combatting false positives and
negatives with including multi-directional tracking and
anti-masking ROIs; combined visualization with SUMA and
AFNI, allowing interactive manipulation of tracking and
regions. These additions to AFNI-FATCAT increase
researchers' capabilities for integrating functional and
diffusion-based tractographic connectivity.
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