ÆÈ·Î¿ì
Ye Wu
Á¦¸ñ
Àοë
Àοë
¿¬µµ
The challenge of mapping the human connectome based on diffusion tractography
KH Maier-Hein, PF Neher, JC Houde, MA Côté, E Garyfallidis, J Zhong, ...
Nature communications 8 (1), 1349, 2017
9752017
An anatomically curated fiber clustering white matter atlas for consistent white matter tract parcellation across the lifespan
F Zhang, Y Wu, I Norton, L Rigolo, Y Rathi, N Makris, LJ O'Donnell
NeuroImage 179, 429-447, 2018
1492018
Tractography-based connectomes are dominated by false-positive connections
KH Maier-Hein, P Neher, JC Houde, MA Côté, E Garyfallidis, J Zhong, ...
BioRxiv, 084137, 2016
672016
Test–retest reproducibility of white matter parcellation using diffusion MRI tractography fiber clustering
F Zhang, Y Wu, I Norton, Y Rathi, AJ Golby, LJ O'Donnell
Human brain mapping 40 (10), 3041-3057, 2019
532019
Tractography reproducibility challenge with empirical data (TraCED): the 2017 ISMRM diffusion study group challenge
V Nath, KG Schilling, P Parvathaneni, Y Huo, JA Blaber, AE Hainline, ...
Journal of Magnetic Resonance Imaging 51 (1), 234-249, 2020
402020
The challenge of mapping the human connectome based on diffusion tractography. Nat Commun 8: 1349
KH Maier-Hein, PF Neher, JC Houde, MA Côté, E Garyfallidis, J Zhong, ...
292017
Investigation into local white matter abnormality in emotional processing and sensorimotor areas using an automatically annotated fiber clustering in major depressive disorder
Y Wu, F Zhang, N Makris, Y Ning, I Norton, S She, H Peng, Y Rathi, ...
NeuroImage 181, 16-29, 2018
282018
Multi-site harmonization of diffusion MRI data via method of moments
KM Huynh, G Chen, Y Wu, D Shen, PT Yap
IEEE transactions on medical imaging 38 (7), 1599-1609, 2019
232019
Mitigating gyral bias in cortical tractography via asymmetric fiber orientation distributions
Y Wu, Y Hong, Y Feng, D Shen, PT Yap
Medical image analysis 59, 101543, 2020
222020
Prediction of 7‐year's conversion from subjective cognitive decline to mild cognitive impairment
L Yue, D Hu, H Zhang, J Wen, Y Wu, W Li, L Sun, X Li, J Wang, G Li, ...
Human Brain Mapping 42 (1), 192-203, 2021
212021
A ReliefF-SVM-based method for marking dopamine-based disease characteristics: A study on SWEDD and Parkinson¡¯s disease
L Jin, Q Zeng, J He, Y Feng, S Zhou, Y Wu
Behavioural brain research 356, 400-407, 2019
202019
The challenge of mapping the human connectome based on diffusion tractography. Nat Commun
KH Maier-Hein, PF Neher, JC Houde, MA Côté, E Garyfallidis, J Zhong, ...
Nature Publishing Group 8, 1349, 2017
182017
DeepBundle: fiber bundle parcellation with graph convolution neural networks
F Liu, J Feng, G Chen, Y Wu, Y Hong, PT Yap, D Shen
Graph Learning in Medical Imaging: First International Workshop, GLMI 2019 ¡¦, 2019
162019
Tract dictionary learning for fast and robust recognition of fiber bundles
Y Wu, Y Hong, S Ahmad, W Lin, D Shen, PT Yap, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd ¡¦, 2020
142020
The challenge of mapping the human connectome based on diffusion tractography. Nat Commun 8 (1): 1349
KH Maier-Hein, PF Neher, JC Houde, MA Cote, E Garyfallidis, J Zhong, ...
142017
Asymmetry spectrum imaging for baby diffusion tractography
Y Wu, W Lin, D Shen, PT Yap, ...
Information Processing in Medical Imaging: 26th International Conference ¡¦, 2019
132019
Tractography-based connectomes are dominated by false-positive connections. bioRxiv
K Maier-Hein, P Neher, JC Houde, MA Cote, E Garyfallidis, J Zhong, ...
November, 2016
132016
Probing tissue microarchitecture of the baby brain via spherical mean spectrum imaging
KM Huynh, T Xu, Y Wu, X Wang, G Chen, H Wu, KH Thung, W Lin, ...
IEEE transactions on medical imaging 39 (11), 3607-3618, 2020
122020
Distributed performance of white matter properties in chess players: a DWI study using automated fiber quantification
S Zhou, L Jin, J He, Q Zeng, Y Wu, Z Cao, Y Feng
Brain Research 1700, 9-18, 2018
122018
Can sam segment polyps?
T Zhou, Y Zhang, Y Zhou, Y Wu, C Gong
arXiv preprint arXiv:2304.07583, 2023
112023
ÇöÀç ½Ã½ºÅÛÀÌ ÀÛµ¿µÇÁö ¾Ê½À´Ï´Ù. ³ªÁß¿¡ ´Ù½Ã ½ÃµµÇØ ÁÖ¼¼¿ä.
ÇмúÀÚ·á 1–20