TY - GEN

T1 - Finding significantly connected voxels based on histograms of connection strengths

AU - Kasenburg, Niklas

AU - Pedersen, Morten Vester

AU - Darkner, Sune

PY - 2016

Y1 - 2016

N2 - We explore a new approach for structural connectivity based segmentations of subcortical brain regions. Connectivity based segmentations are usually based on fibre connections from a seed region to predefined target regions. We present a method for finding significantly connected voxels based on the distribution of connection strengths. Paths from seed voxels to all voxels in a target region are obtained from a shortest-path tractography. For each seed voxel we approximate the distribution with a histogram of path scores. We hypothesise that the majority of estimated connections are false-positives and that their connection strength is distributed differently from true-positive connections. Therefore, an empirical null-distribution is defined for each target region as the average normalized histogram over all voxels in the seed region. Single histograms are then tested against the corresponding null-distribution and significance is determined using the false discovery rate (FDR). Segmentations are based on significantly connected voxels and their FDR. In this work we focus on the thalamus and the target regions were chosen by dividing the cortex into a prefrontal/temporal zone, motor zone, somatosensory zone and a parieto-occipital zone. The obtained segmentations consistently show a sparse number of significantly connected voxels that are located near the surface of the anterior thalamus over a population of 38 subjects. textcopyright (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

AB - We explore a new approach for structural connectivity based segmentations of subcortical brain regions. Connectivity based segmentations are usually based on fibre connections from a seed region to predefined target regions. We present a method for finding significantly connected voxels based on the distribution of connection strengths. Paths from seed voxels to all voxels in a target region are obtained from a shortest-path tractography. For each seed voxel we approximate the distribution with a histogram of path scores. We hypothesise that the majority of estimated connections are false-positives and that their connection strength is distributed differently from true-positive connections. Therefore, an empirical null-distribution is defined for each target region as the average normalized histogram over all voxels in the seed region. Single histograms are then tested against the corresponding null-distribution and significance is determined using the false discovery rate (FDR). Segmentations are based on significantly connected voxels and their FDR. In this work we focus on the thalamus and the target regions were chosen by dividing the cortex into a prefrontal/temporal zone, motor zone, somatosensory zone and a parieto-occipital zone. The obtained segmentations consistently show a sparse number of significantly connected voxels that are located near the surface of the anterior thalamus over a population of 38 subjects. textcopyright (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

U2 - 10.1117/12.2216184

DO - 10.1117/12.2216184

M3 - Article in proceedings

SN - 9781510600195

T3 - Progress in Biomedical Optics and Imaging

BT - Medical Imaging 2016

A2 - Styner, Martin A.

A2 - Angelini, Elsa D.

PB - SPIE - International Society for Optical Engineering

Y2 - 27 February 2016 through 3 March 2016

ER -