TY - GEN
T1 - Angular resolution enhancement of diffusion MRI data using inter-subject information transfer
AU - Chen, Geng
AU - Zhang, Pei
AU - Li, Ke
AU - Wee, Chong Yaw
AU - Wu, Yafeng
AU - Shen, Dinggang
AU - Yap, Pew Thian
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - Diffusion magnetic resonance imaging is widely used to investigate diffusion patterns of water molecules in the human brain. It provides information that is useful for tracing axonal bundles and inferring brain connectivity. Diffusion axonal tracing, namely tractography, relies on local directional information provided by the orientation distribution functions (ODFs) estimated at each voxel. To accurately estimate ODFs, data of good signal-to-noise ratio and sufficient angular samples are desired, but unfortunately, are not always practically available. In this paper, we propose to improve ODF estimation by using inter-subject correlation. Specifically, diffusion-weighted images acquired from different subjects, when transformed to the space of a target subject, can not only provide signal denoising with additional information, but also drastically increase the number of angular samples for better ODF estimation. This is largely because of the incoherence of the angular samples generated when the diffusion signals are reoriented and warped to the target space. Experiments on both synthetic data and real data show that our method can reduce noise-induced artifacts, such as spurious ODF peaks, and yield more coherent orientations.
AB - Diffusion magnetic resonance imaging is widely used to investigate diffusion patterns of water molecules in the human brain. It provides information that is useful for tracing axonal bundles and inferring brain connectivity. Diffusion axonal tracing, namely tractography, relies on local directional information provided by the orientation distribution functions (ODFs) estimated at each voxel. To accurately estimate ODFs, data of good signal-to-noise ratio and sufficient angular samples are desired, but unfortunately, are not always practically available. In this paper, we propose to improve ODF estimation by using inter-subject correlation. Specifically, diffusion-weighted images acquired from different subjects, when transformed to the space of a target subject, can not only provide signal denoising with additional information, but also drastically increase the number of angular samples for better ODF estimation. This is largely because of the incoherence of the angular samples generated when the diffusion signals are reoriented and warped to the target space. Experiments on both synthetic data and real data show that our method can reduce noise-induced artifacts, such as spurious ODF peaks, and yield more coherent orientations.
UR - http://www.scopus.com/inward/record.url?scp=84964060169&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-28588-7_13
DO - 10.1007/978-3-319-28588-7_13
M3 - 会议稿件
AN - SCOPUS:84964060169
SN - 9783319285863
T3 - Mathematics and Visualization
SP - 145
EP - 157
BT - Computational Diffusion MRI - MICCAI Workshop, 2015
A2 - Rathi, Yogesh
A2 - Fuster, Andrea
A2 - Ghosh, Aurobrata
A2 - Kaden, Enrico
A2 - Reisert, Marco
PB - Springer Heidelberg
T2 - Workshop on Computational Diffusion MRI, MICCAI 2015
Y2 - 9 October 2015 through 9 October 2015
ER -