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20112023
most citedA review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises

1.1k citations · 1.4k across the 38 of their papers we have counts for

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Showing 2022Show all

7 papers · 1 filter

eess.IV2022★ 1 cited

HACA3: A Unified Approach for Multi-site MR Image Harmonization

Lianrui Zuo, Yihao Liu, Yuan Xue +10

The lack of standardization is a prominent issue in magnetic resonance (MR) imaging. This often causes undesired contrast variations in the acquired images due to differences in ha…

eess.IV2022★ 2 cited

On Finite Difference Jacobian Computation in Deformable Image Registration

Yihao Liu, Junyu Chen, Shuwen Wei +2

Producing spatial transformations that are diffeomorphic is a key goal in deformable image registration. As a diffeomorphic transformation should have positive Jacobian determinant…

eess.IV2022

Deep filter bank regression for super-resolution of anisotropic MR brain images

Samuel W. Remedios, Shuo Han, Yuan Xue +4

In 2D multi-slice magnetic resonance (MR) acquisition, the through-plane signals are typically of lower resolution than the in-plane signals. While contemporary super-resolution (S…

cs.SD2022

Tagged-MRI Sequence to Audio Synthesis via Self Residual Attention Guided Heterogeneous Translator

Xiaofeng Liu, Fangxu Xing, Jerry L. Prince +4

Understanding the underlying relationship between tongue and oropharyngeal muscle deformation seen in tagged-MRI and intelligible speech plays an important role in advancing speech…

eess.IV2022

Disentangling A Single MR Modality

Lianrui Zuo, Yihao Liu, Yuan Xue +5

Disentangling anatomical and contrast information from medical images has gained attention recently, demonstrating benefits for various image analysis tasks. Current methods learn…

eess.IV2022

Coordinate Translator for Learning Deformable Medical Image Registration

Yihao Liu, Lianrui Zuo, Shuo Han +3

The majority of deep learning (DL) based deformable image registration methods use convolutional neural networks (CNNs) to estimate displacement fields from pairs of moving and fix…

eess.IV2022

Structure-aware Unsupervised Tagged-to-Cine MRI Synthesis with Self Disentanglement

Xiaofeng Liu, Fangxu Xing, Jerry L. Prince +3

Cycle reconstruction regularized adversarial training -- e.g., CycleGAN, DiscoGAN, and DualGAN -- has been widely used for image style transfer with unpaired training data. Several…