3 citations · 5 across the 11 of their papers we have counts for
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Harmonizing MR Images Across 100+ Scanners: Multi-site Validation with Traveling Subjects and Real-world Protocols
Savannah P. Hays, Lianrui Zuo, Muhammad Faizyab Ali Chaudhary +13
Reliable harmonization of heterogeneous magnetic resonance~(MR) image datasets, especially those acquired in pragmatic clinical trials, is critical to advance multi-center neuroima…
CATNUS: Coordinate-Aware Thalamic Nuclei Segmentation Using T1-Weighted MRI
Anqi Feng, Zhangxing Bian, Samuel W. Remedios +6
Accurate segmentation of thalamic nuclei from magnetic resonance images is important due to the distinct roles of these nuclei in overall brain function and to their differential i…
Segmenting Thalamic Nuclei: T1 Maps Provide a Reliable and Efficient Solution
Anqi Feng, Zhangxing Bian, Samuel W. Remedios +5
Accurate thalamic nuclei segmentation is crucial for understanding neurological diseases, brain functions, and guiding clinical interventions. However, the optimal inputs for segme…
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,…
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…
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…
Revisiting registration-based synthesis: A focus on unsupervised MR image synthesis
Savannah P. Hays, Lianrui Zuo, Yihao Liu +4
Deep learning (DL) has led to significant improvements in medical image synthesis, enabling advanced image-to-image translation to generate synthetic images. However, DL methods fa…
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…
Rapid Brain Meninges Surface Reconstruction with Layer Topology Guarantee
Peiyu Duan, Yuan Xue, Shuo Han +8
The meninges, located between the skull and brain, are composed of three membrane layers: the pia, the arachnoid, and the dura. Reconstruction of these layers can aid in studying v…
Optimal operating MR contrast for brain ventricle parcellation
Savannah P. Hays, Lianrui Zuo, Yuli Wang +3
Development of MR harmonization has enabled different contrast MRIs to be synthesized while preserving the underlying anatomy. In this paper, we use image harmonization to explore…
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…