50 citations · 80 across the 5 of their papers we have counts for
5 papers
Reconstruction of Cortical Surfaces with Spherical Topology from Infant Brain MRI via Recurrent Deformation Learning
Xiaoyang Chen, Junjie Zhao, Siyuan Liu +2
Cortical surface reconstruction (CSR) from MRI is key to investigating brain structure and function. While recent deep learning approaches have significantly improved the speed of…
Brain Tissue Segmentation Across the Human Lifespan via Supervised Contrastive Learning
Xiaoyang Chen, Jinjian Wu, Wenjiao Lyu +6
Automatic segmentation of brain MR images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is critical for tissue volumetric analysis and cortical surface re…
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…
Learning Multi-Site Harmonization of Magnetic Resonance Images Without Traveling Human Phantoms
Siyuan Liu, Pew-Thian Yap
Harmonization improves data consistency and is central to effective integration of diverse imaging data acquired across multiple sites. Recent deep learning techniques for harmoniz…
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…