David Raffelt1,2, J-Donald Tournier3,4,
Gerard Ridgway5, Stephen Rose6, Robert Henderson7,
Stuart Crozier2, Alan Connelly3,4, Olivier Salvado1
1The Australian E-Health
Research Centre, CSIRO, Brisbane, QLD, Australia; 2Biomedical
Engineering, School of ITEE, University of Queensland, Brisbane, QLD,
Australia; 3Brain Research Institute, Florey Neuroscience
Institutes (Austin), Melbourne, VIC, Australia; 4Department of
Medicine, University of Melbourne, Melbourne, VIC, Australia; 5Institute
of Neurology, University College London, London, United Kingdom; 6Centre
for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia; 7Department
of Neurology, Royal Brisbane & Women's Hospital, Brisbane, QLD, Australia
Apparent Fibre Density (AFD) is a new measure based on information provided by Fibre Orientation Distributions. AFD enables voxel-based analysis to be performed over space and orientation, and therefore population differences may be attributed to a single fibre within a voxel containing multiple fibres. Performing comparisons over many orientations within each voxel increases the number of multiple comparisons. We present a method for cluster-based inference of spatially extended differences in AFD by identifying clusters of contiguous supra-threshold directions using neighbours defined in space and orientation. The proposed method is demonstrated using a cohort of Motor Neurone Disease and healthy subjects.
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