387 citations · 509 across the 50 of their papers we have counts for
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Solving a Nonlinear Blind Inverse Problem for Tagged MRI with Physics and Deep Generative Priors
Zhangxing Bian, Shuwen Wei, Samuel W. Remedios +4
Tagged MRI enables tracking internal tissue motion non-invasively. It encodes motion by modulating anatomy with periodic tags, which deform along with tissue. However, the entangle…
MedForj: An open, large-scale foundational generative prior for high-resolution 3D brain MRI
Samuel W. Remedios, Aaron Carass, Jerry L. Prince +1
This work introduces MedForj, a suite of 3D foundational generative priors based on diffusion models. The MedForj models were trained on 1~mm isotropic 3D -weighted…
Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges
Lasse Hansen, Wiebke Heyer, Christoph Großbröhmer +51
Medical image registration is critical for clinical applications, and fair benchmarking of different methods is essential for monitoring ongoing progress in the field. To date, the…
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…
Brightness-Invariant Tracking Estimation in Tagged MRI
Zhangxing Bian, Shuwen Wei, Xiao Liang +10
Magnetic resonance (MR) tagging is an imaging technique for noninvasively tracking tissue motion in vivo by creating a visible pattern of magnetization saturation (tags) that defor…
Beyond the LUMIR challenge: The pathway to foundational registration models
Junyu Chen, Shuwen Wei, Joel Honkamaa +33
Medical image challenges have played a transformative role in advancing the field, catalyzing innovation and establishing new performance benchmarks. Image registration, a foundati…
Correlation Ratio for Unsupervised Learning of Multi-modal Deformable Registration
Xiaojian Chen, Yihao Liu, Shuwen Wei +3
In recent years, unsupervised learning for deformable image registration has been a major research focus. This approach involves training a registration network using pairs of movi…
Unique MS Lesion Identification from MRI
Carlos A. Rivas, Jinwei Zhang, Shuwen Wei +3
Unique identification of multiple sclerosis (MS) white matter lesions (WMLs) is important to help characterize MS progression. WMLs are routinely identified from magnetic resonance…
Bi-Directional MS Lesion Filling and Synthesis Using Denoising Diffusion Implicit Model-based Lesion Repainting
Jinwei Zhang, Lianrui Zuo, Yihao Liu +4
Automatic magnetic resonance (MR) image processing pipelines are widely used to study people with multiple sclerosis (PwMS), encompassing tasks such as lesion segmentation and brai…
Unsupervised Learning of Multi-modal Affine Registration for PET/CT
Junyu Chen, Yihao Liu, Shuwen Wei +2
Affine registration plays a crucial role in PET/CT imaging, where aligning PET with CT images is challenging due to their respective functional and anatomical representations. Desp…
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…
From Registration Uncertainty to Segmentation Uncertainty
Junyu Chen, Yihao Liu, Shuwen Wei +3
Understanding the uncertainty inherent in deep learning-based image registration models has been an ongoing area of research. Existing methods have been developed to quantify both…
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…
Is Registering Raw Tagged-MR Enough for Strain Estimation in the Era of Deep Learning?
Zhangxing Bian, Ahmed Alshareef, Shuwen Wei +7
Magnetic Resonance Imaging with tagging (tMRI) has long been utilized for quantifying tissue motion and strain during deformation. However, a phenomenon known as tag fading, a grad…
AniRes2D: Anisotropic Residual-enhanced Diffusion for 2D MR Super-Resolution
Zejun Wu, Samuel W. Remedios, Blake E. Dewey +2
Anisotropic low-resolution (LR) magnetic resonance (MR) images are fast to obtain but hinder automated processing. We propose to use denoising diffusion probabilistic models (DDPMs…
Towards an accurate and generalizable multiple sclerosis lesion segmentation model using self-ensembled lesion fusion
Jinwei Zhang, Lianrui Zuo, Blake E. Dewey +4
Automatic multiple sclerosis (MS) lesion segmentation using multi-contrast magnetic resonance (MR) images provides improved efficiency and reproducibility compared to manual deline…
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…
MomentaMorph: Unsupervised Spatial-Temporal Registration with Momenta, Shooting, and Correction
Zhangxing Bian, Shuwen Wei, Yihao Liu +6
Tagged magnetic resonance imaging (tMRI) has been employed for decades to measure the motion of tissue undergoing deformation. However, registration-based motion estimation from tM…
A survey on deep learning in medical image registration: new technologies, uncertainty, evaluation metrics, and beyond
Junyu Chen, Yihao Liu, Shuwen Wei +5
Deep learning technologies have dramatically reshaped the field of medical image registration over the past decade. The initial developments, such as regression-based and U-Net-bas…
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…
DrDisco: Deep Registration for Distortion Correction of Diffusion MRI with single phase-encoding
Zhangxing Bian, Muhan Shao, Aaron Carass +1
Diffusion-weighted magnetic resonance imaging (DW-MRI) is a non-invasive way of imaging white matter tracts in the human brain. DW-MRIs are usually acquired using echo-planar imagi…
Label Propagation via Random Walk for Training Robust Thalamus Nuclei Parcellation Model from Noisy Annotations
Anqi Feng, Yuan Xue, Yuli Wang +7
Data-driven thalamic nuclei parcellation depends on high-quality manual annotations. However, the small size and low contrast changes among thalamic nuclei, yield annotations that…