1 citations · 1 across the 12 of their papers we have counts for
12 papers
Harmonizing MR Images Across 100+ Scanners: Multi-site Validation with Traveling Subjects and Real-world Protocols
Savannah P. Hays, Lianrui Zuo, Muhammad Faizyab Ali Chaudhary +13
Reliable harmonization of heterogeneous magnetic resonance~(MR) image datasets, especially those acquired in pragmatic clinical trials, is critical to advance multi-center neuroima…
CATNUS: Coordinate-Aware Thalamic Nuclei Segmentation Using T1-Weighted MRI
Anqi Feng, Zhangxing Bian, Samuel W. Remedios +6
Accurate segmentation of thalamic nuclei from magnetic resonance images is important due to the distinct roles of these nuclei in overall brain function and to their differential i…
Segmenting Thalamic Nuclei: T1 Maps Provide a Reliable and Efficient Solution
Anqi Feng, Zhangxing Bian, Samuel W. Remedios +5
Accurate thalamic nuclei segmentation is crucial for understanding neurological diseases, brain functions, and guiding clinical interventions. However, the optimal inputs for segme…
Synthetic multi-inversion time magnetic resonance images for visualization of subcortical structures
Savannah P. Hays, Lianrui Zuo, Anqi Feng +7
Purpose: Visualization of subcortical gray matter is essential in neuroscience and clinical practice, particularly for disease understanding and surgical planning.While multi-inver…
Brightness-Invariant Tracking Estimation in Tagged MRI
Zhangxing Bian, Shuwen Wei, Xiao Liang +10
Magnetic resonance (MR) tagging is an imaging technique for noninvasively tracking tissue motion in vivo by creating a visible pattern of magnetization saturation (tags) that defor…
A Speech-to-Video Synthesis Approach Using Spatio-Temporal Diffusion for Vocal Tract MRI
Paula Andrea Pérez-Toro, Tomás Arias-Vergara, Fangxu Xing +9
Understanding the relationship between vocal tract motion during speech and the resulting acoustic signal is crucial for aided clinical assessment and developing personalized treat…
RATNUS: Rapid, Automatic Thalamic Nuclei Segmentation using Multimodal MRI inputs
Anqi Feng, Zhangxing Bian, Blake E. Dewey +3
Accurate segmentation of thalamic nuclei is important for better understanding brain function and improving disease treatment. Traditional segmentation methods often rely on a sing…
Revisiting registration-based synthesis: A focus on unsupervised MR image synthesis
Savannah P. Hays, Lianrui Zuo, Yihao Liu +4
Deep learning (DL) has led to significant improvements in medical image synthesis, enabling advanced image-to-image translation to generate synthetic images. However, DL methods fa…
Speech motion anomaly detection via cross-modal translation of 4D motion fields from tagged MRI
Xiaofeng Liu, Fangxu Xing, Jiachen Zhuo +4
Understanding the relationship between tongue motion patterns during speech and their resulting speech acoustic outcomes -- i.e., articulatory-acoustic relation -- is of great impo…
Is Registering Raw Tagged-MR Enough for Strain Estimation in the Era of Deep Learning?
Zhangxing Bian, Ahmed Alshareef, Shuwen Wei +7
Magnetic Resonance Imaging with tagging (tMRI) has long been utilized for quantifying tissue motion and strain during deformation. However, a phenomenon known as tag fading, a grad…
Speech Audio Synthesis from Tagged MRI and Non-Negative Matrix Factorization via Plastic Transformer
Xiaofeng Liu, Fangxu Xing, Maureen Stone +5
The tongue's intricate 3D structure, comprising localized functional units, plays a crucial role in the production of speech. When measured using tagged MRI, these functional units…
Attentive Continuous Generative Self-training for Unsupervised Domain Adaptive Medical Image Translation
Xiaofeng Liu, Jerry L. Prince, Fangxu Xing +5
Self-training is an important class of unsupervised domain adaptation (UDA) approaches that are used to mitigate the problem of domain shift, when applying knowledge learned from a…