3 citations · 4 across the 5 of their papers we have counts for
6 papers · 1 filter
MSRepaint: Multiple Sclerosis Repaint with Conditional Denoising Diffusion Implicit Model for Bidirectional Lesion Filling and Synthesis
Jinwei Zhang, Lianrui Zuo, Yihao Liu +10
In multiple sclerosis, lesions interfere with automated magnetic resonance imaging analyses such as brain parcellation and deformable registration, while lesion segmentation models…
UNISELF: A Unified Network with Instance Normalization and Self-Ensembled Lesion Fusion for Multiple Sclerosis Lesion Segmentation
Jinwei Zhang, Lianrui Zuo, Blake E. Dewey +9
Automated segmentation of multiple sclerosis (MS) lesions using multicontrast magnetic resonance (MR) images improves efficiency and reproducibility compared to manual delineation,…
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…
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…
Towards an accurate and generalizable multiple sclerosis lesion segmentation model using self-ensembled lesion fusion
Jinwei Zhang, Lianrui Zuo, Blake E. Dewey +4
Automatic multiple sclerosis (MS) lesion segmentation using multi-contrast magnetic resonance (MR) images provides improved efficiency and reproducibility compared to manual deline…
Harmonization-enriched domain adaptation with light fine-tuning for multiple sclerosis lesion segmentation
Jinwei Zhang, Lianrui Zuo, Blake E. Dewey +5
Deep learning algorithms utilizing magnetic resonance (MR) images have demonstrated cutting-edge proficiency in autonomously segmenting multiple sclerosis (MS) lesions. Despite the…