Zobrazeno 1 - 10
of 14
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
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
Autor:
Jiliu Zhou, Biting Yu, David S. Lalush, Xi Wu, Weili Lin, Yan Wang, Lei Wang, Dinggang Shen, Luping Zhou, Chen Zu
Publikováno v:
IEEE Transactions on Medical Imaging. 38:1328-1339
Positron emission tomography (PET) has been substantially used recently. To minimize the potential health risk caused by the tracer radiation inherent to PET scans, it is of great interest to synthesize the high-quality PET image from the low-dose on
Publikováno v:
IEEE Transactions on Cybernetics. 49:1123-1136
Accurate segmentation of infant brain images into different regions of interest is one of the most important fundamental steps in studying early brain development. In the isointense phase (approximately 6–8 months of age), white matter and gray mat
Publikováno v:
IEEE Access, Vol 7, Pp 33728-33740 (2019)
Hippocampal segmentation from infant brain MR images is indispensable for studying early brain development. However, most of the hippocampal segmentation methods were developed for population-based adult brain images, which are not suitable for longi
Publikováno v:
IEEE Transactions on Biomedical Engineering. 64:2803-2812
Objective: The goal of this paper is to automatically segment perivascular spaces (PVSs) in brain from high-resolution 7T magnetic resonance (MR) images. Methods: We propose a structured-learning-based segmentation framework to extract the PVSs from
Publikováno v:
IEEE Transactions on Biomedical Engineering. 67:2705-2705