activity
20222025
most citedUNISELF: A Unified Network with Instance Normalization and Self-Ensembled Lesion Fusion for Multiple Sclerosis Lesion Segmentation

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

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,…

eess.IV2025

Synthetic multi-inversion time magnetic resonance images for visualization of subcortical structures

Savannah P. Hays, Lianrui Zuo, Anqi Feng +7

Purpose: Visualization of subcortical gray matter is essential in neuroscience and clinical practice, particularly for disease understanding and surgical planning.While multi-inver…

stat.AP2024

Hazard and Beyond: Exploring Five Distributional Representations of Accelerometry Data for Disability Discrimination in Multiple Sclerosis

Pratim Guha Niyogi, Muraleetharan Sanjayan, Dmitri Volfson +3

Research on modeling the distributional aspects in sensor-based digital health (sDHT) data has grown significantly in recent years. Most existing approaches focus on using individu…

eess.IV2024

Beyond MR Image Harmonization: Resolution Matters Too

Savannah P. Hays, Samuel W. Remedios, Lianrui Zuo +6

Magnetic resonance (MR) imaging is commonly used in the clinical setting to non-invasively monitor the body. There exists a large variability in MR imaging due to differences in sc…

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…