TY  - GEN
EP  - 5
N1  - This version is the author-accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
ID  - discovery10200545
AV  - public
KW  - Atrophy
KW  -  Neuroimaging
KW  -  Image segmentation
KW  -  Multiple sclerosis
KW  -  Image resolution
KW  -  Magnetic resonance imaging
KW  -  White matter
PB  - IEEE
SN  - 1945-7928
A1  - Laso, Pablo
A1  - Cerri, Stefano
A1  - Sorby-Adams, Annabel
A1  - Guo, Jennifer
A1  - Mateen, Farrah
A1  - Goebl, Philipp
A1  - Wu, Jiaming
A1  - Liu, Peirong
A1  - Li, Hongwei B
A1  - Young, Sean I
A1  - Billot, Benjamin
A1  - Puonti, Oula
A1  - Sze, Gordon
A1  - Payabavash, Sam
A1  - Dehavenon, Adam
A1  - Sheth, Kevin N
A1  - Rosen, Matthew  S
A1  - Kirsch, John
A1  - Strisciuglio, Nicola
A1  - Wolterink, Jelmer M
A1  - Eshaghi, Arman
A1  - Barkhof, Frederik
A1  - Kimberly, W Taylor
A1  - Iglesias, Juan Eugenio
Y1  - 2024/08/22/
UR  - https://doi.org/10.1109/ISBI56570.2024.10635502
N2  - Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis. Automated segmentation and quantification is desirable but existing methods require high-resolution MRI with good signal-to-noise ratio (SNR). This precludes application to clinical and low-field portable MRI (pMRI) scans, thus hampering large-scale tracking of atrophy and WMH progression, especially in underserved areas where pMRI has huge potential. Here we present a method that segments white matter hyperintensity and 36 brain regions from scans of any resolution and contrast (including pMRI) without retraining. We show results on eight public datasets and on a private dataset with paired high- and low-field scans (3T and 64mT), where we attain strong correlation between the WMH (?=.85) and hippocampal volumes (?=.89) estimated at both fields. Our method is publicly available as part of FreeSurfer, at: http://surfer.nmr.mgh.harvard.edu/fswiki/WMH-SynthSeg.
SP  - 1
CY  - Athens, Greece
TI  - Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI
T3  - IEEE International Symposium on Biomedical Imaging (ISBI)
ER  -