21 citations · 48 across the 6 of their papers we have counts for
6 papers
Contrast-Invariant Self-supervised Segmentation for Quantitative Placental MRI
Xinliu Zhong, Ruiying Liu, Emily S. Nichols +4
Accurate placental segmentation is essential for quantitative analysis of the placenta. However, this task is particularly challenging in T2*-weighted placental imaging due to: (1)…
Robust Quantification of Percent Emphysema on CT via Domain Attention: the Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study
Xuzhe Zhang, Elsa D. Angelini, Eric A. Hoffman +4
Robust quantification of pulmonary emphysema on computed tomography (CT) remains challenging for large-scale research studies that involve scans from different scanner types and fo…
MAPSeg: Unified Unsupervised Domain Adaptation for Heterogeneous Medical Image Segmentation Based on 3D Masked Autoencoding and Pseudo-Labeling
Xuzhe Zhang, Yuhao Wu, Elsa Angelini +10
Robust segmentation is critical for deriving quantitative measures from large-scale, multi-center, and longitudinal medical scans. Manually annotating medical scans, however, is ex…
Improving Across-Dataset Brain Tissue Segmentation Using Transformer
Vishwanatha M. Rao, Zihan Wan, Soroush Arabshahi +6
Brain tissue segmentation has demonstrated great utility in quantifying MRI data through Voxel-Based Morphometry and highlighting subtle structural changes associated with various…
Recursive Refinement Network for Deformable Lung Registration between Exhale and Inhale CT Scans
Xinzi He, Jia Guo, Xuzhe Zhang +9
Unsupervised learning-based medical image registration approaches have witnessed rapid development in recent years. We propose to revisit a commonly ignored while simple and well-e…
PTNet: A High-Resolution Infant MRI Synthesizer Based on Transformer
Xuzhe Zhang, Xinzi He, Jia Guo +6
Magnetic resonance imaging (MRI) noninvasively provides critical information about how human brain structures develop across stages of life. Developmental scientists are particular…