Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Weili Lin"'
Autor:
Dongming Wei, Sahar Ahmad, Yuyu Guo, Liyun Chen, Yunzhi Huang, Lei Ma, Zhengwang Wu, Gang Li, Li Wang, Weili Lin, Pew-Thian Yap, Dinggang Shen, Qian Wang
Publikováno v:
IEEE Trans Med Imaging
Deformable registration is fundamental to longitudinal and population-based image analyses. However, it is challenging to precisely align longitudinal infant brain MR images of the same subject, as well as cross-sectional infant brain MR images of di
Autor:
Li Wang, Gang Li, Zhengwang Wu, Fenqiang Zhao, Fan Wang, Weili Lin, Dinggang Shen, Shunren Xia
Publikováno v:
IEEE Trans Med Imaging
Cortical surface registration is an essential step and prerequisite for surface-based neuroimaging analysis. It aligns cortical surfaces across individuals and time points to establish cross-sectional and longitudinal cortical correspondences to faci
Autor:
Li Zhao, Toan Duc Bui, Qi Dou, Yu Zhang, Sijie Niu, Trung Le Phan, Guannan Li, Longchuan Li, Sarah Shultz, Xiaopeng Zong, Wenao Ma, Gang Li, Yue Sun, Ying Wei, Xue Feng, Mallappa Kumara Swamy, Camilo Bermudez Noguera, Tao Zhong, Valerie Jewells, Li Wang, Weili Lin, Ramesh Basnet, Caizi Li, M. Omair Ahmad, Dinggang Shen, Zhihao Lei, Ian H. Gotlib, Kathryn L. Humphreys, Jun Ma, Bennett A. Landman, Jitae Shin, Kun Gao, Zhengwang Wu, Lequan Yu, Xiaoping Yang
Publikováno v:
IEEE Trans Med Imaging
To better understand early brain development in health and disorder, it is critical to accurately segment infant brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). Deep learning-based methods
Autor:
Yu Li, Xin Zhang, Jingxin Nie, Guowei Zhang, Ruiyan Fang, Xiangmin Xu, Zhengwang Wu, Dan Hu, Li Wang, Han Zhang, Weili Lin, Gang Li
Publikováno v:
IEEE transactions on medical imaging. 41(10)
Infancy is a critical period for the human brain development, and brain age is one of the indices for the brain development status associated with neuroimaging data. The difference between the predicted age based on neuroimaging and the chronological
Publikováno v:
IEEE transactions on medical imaging
Fast and automated image quality assessment (IQA) for diffusion MR images is a crucial step for swiftly making a rescan decision during or after the scanning session. However, learning a model for this task is challenging as the number of annotated d
Autor:
Jiale Cheng, Xin Zhang, Hao Ni, Chenyang Li, Xiangmin Xu, Zhengwang Wu, Li Wang, Weili Lin, Gang Li
Publikováno v:
IEEE Trans Med Imaging
Studies have shown that there is a tight connection between cognition skills and brain morphology during infancy. Nonetheless, it is still a great challenge to predict individual cognitive scores using their brain morphological features, considering
Autor:
Shunren Xia, Li Wang, Dingna Duan, John H. Gilmore, Zhengwang Wu, Dinggang Shen, Islem Rekik, Gang Li, Weili Lin
Publikováno v:
Human Brain Mapping. 41:1985-2003
Studying the early dynamic development of cortical folding with remarkable individual variability is critical for understanding normal early brain development and related neurodevelopmental disorders. This study focuses on the fingerprinting capabili
Publikováno v:
IEEE Trans Med Imaging
Missing data is a common problem in longitudinal studies due to subject dropouts and failed scans. We present a graph-based convolutional neural network to predict missing diffusion MRI data. In particular, we consider the relationships between sampl
Publikováno v:
IEEE Trans Med Imaging
Diffusion magnetic resonance imaging (DMRI) suffers from lower signal-to-noise-ratio (SNR) due to MR signal attenuation associated with the motion of water molecules. To improve SNR, the non-local means (NLM) algorithm has demonstrated state-of-the-a
Publikováno v:
Med Image Anal
Diffusion MRI (DMRI) is a powerful tool for studying early brain development and disorders. However, the typically low spatio-angular resolution of DMRI diminishes structural details and limits quantitative analysis to simple diffusion models. This p