TY - GEN
T1 - Resolution enhancement of diffusion-weighted images by local fiber profiling
AU - Yap, Pew Thian
AU - Shen, Dinggang
N1 - Funding Information:
Acknowledgment. This work was supported in part by a UNC start-up fund and NIH grants (EB006733, EB008374, EB009634, MH088520, and AG041721).
Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2012.
PY - 2012
Y1 - 2012
N2 - Diffusion-weighted imaging (DWI), while giving rich information about brain circuitry, is often limited by insufficient spatial resolution and low signal-to-noise ratio (SNR). This paper describes an algorithm that will increase the resolution of DW images beyond the scan resolution, allowing for a closer investigation of fiber structures and more accurate assessment of brain connectivity. The algorithm is capable of generating a dense vector-valued field, consisting of diffusion data associated with the full set of diffusion-sensitizing gradients. The fundamental premise is that, to best preserve information, interpolation should always be performed along fiber streamlines. To achieve this, at each spatial location, we probe neighboring voxels in various directions to gather diffusion information for data reconstruction. Based on the fiber orientation distribution (FOD), directions that are more likely to be traversed by fibers will be given greater weights during interpolation and vice versa. This ensures that data reconstruction is only contributed by diffusion data coming from fibers that are aligned with a specific direction. This approach respects local fiber structures and prevents blurring resulting from averaging of data from significantly misaligned fibers. Evaluations suggest that this algorithm yields results with significantly less blocking artifacts, greater smoothness in anatomical structures, and markedly improved structural visibility.
AB - Diffusion-weighted imaging (DWI), while giving rich information about brain circuitry, is often limited by insufficient spatial resolution and low signal-to-noise ratio (SNR). This paper describes an algorithm that will increase the resolution of DW images beyond the scan resolution, allowing for a closer investigation of fiber structures and more accurate assessment of brain connectivity. The algorithm is capable of generating a dense vector-valued field, consisting of diffusion data associated with the full set of diffusion-sensitizing gradients. The fundamental premise is that, to best preserve information, interpolation should always be performed along fiber streamlines. To achieve this, at each spatial location, we probe neighboring voxels in various directions to gather diffusion information for data reconstruction. Based on the fiber orientation distribution (FOD), directions that are more likely to be traversed by fibers will be given greater weights during interpolation and vice versa. This ensures that data reconstruction is only contributed by diffusion data coming from fibers that are aligned with a specific direction. This approach respects local fiber structures and prevents blurring resulting from averaging of data from significantly misaligned fibers. Evaluations suggest that this algorithm yields results with significantly less blocking artifacts, greater smoothness in anatomical structures, and markedly improved structural visibility.
UR - http://www.scopus.com/inward/record.url?scp=84872921731&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33454-2_3
DO - 10.1007/978-3-642-33454-2_3
M3 - Conference contribution
C2 - 23286109
AN - SCOPUS:84872921731
SN - 9783642334535
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 18
EP - 25
BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI2012 - 15th International Conference, Proceedings
A2 - Ayache, Nicholas
A2 - Delingette, Herve
A2 - Golland, Polina
A2 - Mori, Kensaku
PB - Springer Verlag
T2 - 15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012
Y2 - 1 October 2012 through 5 October 2012
ER -