110 citations · 235 across the 12 of their papers we have counts for
12 papers
Learning MRI Artifact Removal With Unpaired Data
Siyuan Liu, Kim-Han Thung, Liangqiong Qu +3
Retrospective artifact correction (RAC) improves image quality post acquisition and enhances image usability. Recent machine learning driven techniques for RAC are predominantly ba…
A Few-shot Learning Graph Multi-Trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint
Alaa Bessadok, Ahmed Nebli, Mohamed Ali Mahjoub +4
Charting the baby connectome evolution trajectory during the first year after birth plays a vital role in understanding dynamic connectivity development of baby brains. Such analys…
Navigator-Free Submillimeter Diffusion Imaging using Multishot-encoded Simultaneous Multi-slice (MUSIUM)
Wei-Tang Chang, Khoi Minh Huynh, Pew-Thian Yap +1
The ability to achieve submillimter isotropic resolution diffusion MR imaging (dMRI) is critically important to study fine-scale brain structures, particularly in the cortex. One o…
Co-evolution of Functional Brain Network at Multiple Scales during Early Infancy
Xuyun Wen, Liming Hsu, Weili Lin +2
The human brains are organized into hierarchically modular networks facilitating efficient and stable information processing and supporting diverse cognitive processes during the c…
Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge
Yue Sun, Kun Gao, Zhengwang Wu +30
To better understand early brain growth patterns in health and disorder, it is critical to accurately segment infant brain magnetic resonance (MR) images into white matter (WM), gr…
Multifold Acceleration of Diffusion MRI via Slice-Interleaved Diffusion Encoding (SIDE)
Yoonmi Hong, Wei-Tang Chang, Geng Chen +4
Diffusion MRI (dMRI) is a unique imaging technique for in vivo characterization of tissue microstructure and white matter pathways. However, its relatively long acquisition time im…
Probing Tissue Microarchitecture of the Baby Brain via Spherical Mean Spectrum Imaging
Khoi Minh Huynh, Tiantian Xu, Ye Wu +7
During the first years of life, the human brain undergoes dynamic spatially-heterogeneous changes, involving differentiation of neuronal types, dendritic arborization, axonal ingro…
FRNET: Flattened Residual Network for Infant MRI Skull Stripping
Qian Zhang, Li Wang, Xiaopeng Zong +3
Skull stripping for brain MR images is a basic segmentation task. Although many methods have been proposed, most of them focused mainly on the adult MR images. Skull stripping for…
Real-Time Quality Assessment of Pediatric MRI via Semi-Supervised Deep Nonlocal Residual Neural Networks
Siyuan Liu, Kim-Han Thung, Weili Lin +2
In this paper, we introduce an image quality assessment (IQA) method for pediatric T1- and T2-weighted MR images. IQA is first performed slice-wise using a nonlocal residual neural…
Spherical U-Net on Cortical Surfaces: Methods and Applications
Fenqiang Zhao, Shunren Xia, Zhengwang Wu +6
Convolutional Neural Networks (CNNs) have been providing the state-of-the-art performance for learning-related problems involving 2D/3D images in Euclidean space. However, unlike i…
Angular Upsampling in Infant Diffusion MRI Using Neighborhood Matching in x-q Space
Geng Chen, Bin Dong, Yong Zhang +3
Diffusion MRI requires sufficient coverage of the diffusion wavevector space, also known as the q-space, to adequately capture the pattern of water diffusion in various directions…
Multiscale adaptive smoothing models for the hemodynamic response function in fMRI
Jiaping Wang, Hongtu Zhu, Jianqing Fan +2
In the event-related functional magnetic resonance imaging (fMRI) data analysis, there is an extensive interest in accurately and robustly estimating the hemodynamic response funct…