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20192026
most citedGeometric Loss for Deep Multiple Sclerosis lesion Segmentation

21 citations · 111 across the 32 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

eess.IV2025

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…

cs.CV2025★ 4 cited

Encoder-Only Image Registration

Xiang Chen, Renjiu Hu, Jinwei Zhang +5

Learning-based techniques have significantly improved the accuracy and speed of deformable image registration. However, challenges such as reducing computational complexity and han…

eess.IV2025★ 3 cited

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,…

cs.CV2025

Unsupervised Deformable Image Registration with Structural Nonparametric Smoothing

Hang Zhang, Xiang Chen, Renjiu Hu +7

Learning-based deformable image registration (DIR) accelerates alignment by amortizing traditional optimization via neural networks. Label supervision further enhances accuracy, en…

cs.CV2025★ 1 cited

ECLARE: Efficient cross-planar learning for anisotropic resolution enhancement

Samuel W. Remedios, Shuwen Wei, Shuo Han +6

In clinical imaging, magnetic resonance (MR) image volumes are often acquired as stacks of 2D slices with decreased scan times, improved signal-to-noise ratio, and image contrasts…