Publications (4)
FlexDTI: Flexible diffusion gradient encoding scheme-based highly efficient diffusion tensor imaging using deep learning
Zejun Wu, Jiechao Wang, Zunquan Chen +9
Objective: Most deep neural network-based diffusion tensor imaging methods require the diffusion gradients' number and directions in the data to be reconstructed to match those in…
AniRes2D: Anisotropic Residual-enhanced Diffusion for 2D MR Super-Resolution
Zejun Wu, Samuel W. Remedios, Blake E. Dewey +2
Anisotropic low-resolution (LR) magnetic resonance (MR) images are fast to obtain but hinder automated processing. We propose to use denoising diffusion probabilistic models (DDPMs…
See More, Change Less: Anatomy-Aware Diffusion for Contrast Enhancement
Junqi Liu, Zejun Wu, Pedro R. A. S. Bassi +15
Image enhancement improves visual quality and helps reveal details that are hard to see in the original image. In medical imaging, it can support clinical decision-making, but curr…
Bridging Synthetic-to-Real Gaps: Frequency-Aware Perturbation and Selection for Single-shot Multi-Parametric Mapping Reconstruction
Linyu Fan, Che Wang, Ming Ye +7
Data-centric artificial intelligence (AI) has remarkably advanced medical imaging, with emerging methods using synthetic data to address data scarcity while introducing synthetic-t…