6 citations · 12 across the 8 of their papers we have counts for
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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…
Diffusion-Driven Generation of Minimally Preprocessed Brain MRI
Samuel W. Remedios, Aaron Carass, Jerry L. Prince +1
The purpose of this study is to present and compare three denoising diffusion probabilistic models (DDPMs) that generate 3D -weighted MRI human brain images. Three DDPMs were…
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…
RATNUS: Rapid, Automatic Thalamic Nuclei Segmentation using Multimodal MRI inputs
Anqi Feng, Zhangxing Bian, Blake E. Dewey +3
Accurate segmentation of thalamic nuclei is important for better understanding brain function and improving disease treatment. Traditional segmentation methods often rely on a sing…