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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…
Attentive Continuous Generative Self-training for Unsupervised Domain Adaptive Medical Image Translation
Xiaofeng Liu, Jerry L. Prince, Fangxu Xing +5
Self-training is an important class of unsupervised domain adaptation (UDA) approaches that are used to mitigate the problem of domain shift, when applying knowledge learned from a…
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…
Automated Ventricle Parcellation and Evan's Ratio Computation in Pre- and Post-Surgical Ventriculomegaly
Yuli Wang, Anqi Feng, Yuan Xue +6
Normal pressure hydrocephalus~(NPH) is a brain disorder associated with enlarged ventricles and multiple cognitive and motor symptoms. The degree of ventricular enlargement can be…
FastCod: Fast Brain Connectivity in Diffusion Imaging
Zhangxing Bian, Muhan Shao, Jiachen Zhuo +3
Connectivity information derived from diffusion-weighted magnetic resonance images~(DW-MRIs) plays an important role in studying human subcortical gray matter structures. However,…
Synthesizing audio from tongue motion during speech using tagged MRI via transformer
Xiaofeng Liu, Fangxu Xing, Jerry L. Prince +3
Investigating the relationship between internal tissue point motion of the tongue and oropharyngeal muscle deformation measured from tagged MRI and intelligible speech can aid in a…
New starting point registration method for tagged MRI tongue motion estimation
Jinglun Yu, Muhan Shao, Zhangxing Bian +4
Accurate tongue motion estimation is essential for tongue function evaluation. The harmonic phase processing (HARP) method and the phase vector incompressible registration algorith…
A latent space for unsupervised MR image quality control via artifact assessment
Lianrui Zuo, Yuan Xue, Blake E. Dewey +3
Image quality control (IQC) can be used in automated magnetic resonance (MR) image analysis to exclude erroneous results caused by poorly acquired or artifact-laden images. Existin…
Segmenting thalamic nuclei from manifold projections of multi-contrast MRI
Chang Yan, Muhan Shao, Zhangxing Bian +6
The thalamus is a subcortical gray matter structure that plays a key role in relaying sensory and motor signals within the brain. Its nuclei can atrophy or otherwise be affected by…
DRIMET: Deep Registration for 3D Incompressible Motion Estimation in Tagged-MRI with Application to the Tongue
Zhangxing Bian, Fangxu Xing, Jinglun Yu +6
Tagged magnetic resonance imaging~(MRI) has been used for decades to observe and quantify the detailed motion of deforming tissue. However, this technique faces several challenges…
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…
On Finite Difference Jacobian Computation in Deformable Image Registration
Yihao Liu, Junyu Chen, Shuwen Wei +2
Producing spatial transformations that are diffeomorphic is a key goal in deformable image registration. As a diffeomorphic transformation should have positive Jacobian determinant…
Deep filter bank regression for super-resolution of anisotropic MR brain images
Samuel W. Remedios, Shuo Han, Yuan Xue +4
In 2D multi-slice magnetic resonance (MR) acquisition, the through-plane signals are typically of lower resolution than the in-plane signals. While contemporary super-resolution (S…
Disentangling A Single MR Modality
Lianrui Zuo, Yihao Liu, Yuan Xue +5
Disentangling anatomical and contrast information from medical images has gained attention recently, demonstrating benefits for various image analysis tasks. Current methods learn…
Coordinate Translator for Learning Deformable Medical Image Registration
Yihao Liu, Lianrui Zuo, Shuo Han +3
The majority of deep learning (DL) based deformable image registration methods use convolutional neural networks (CNNs) to estimate displacement fields from pairs of moving and fix…
Structure-aware Unsupervised Tagged-to-Cine MRI Synthesis with Self Disentanglement
Xiaofeng Liu, Fangxu Xing, Jerry L. Prince +3
Cycle reconstruction regularized adversarial training -- e.g., CycleGAN, DiscoGAN, and DualGAN -- has been widely used for image style transfer with unpaired training data. Several…
Information-based Disentangled Representation Learning for Unsupervised MR Harmonization
Lianrui Zuo, Blake E. Dewey, Aaron Carass +4
Accuracy and consistency are two key factors in computer-assisted magnetic resonance (MR) image analysis. However, contrast variation from site to site caused by lack of standardiz…
Dual-cycle Constrained Bijective VAE-GAN For Tagged-to-Cine Magnetic Resonance Image Synthesis
Xiaofeng Liu, Fangxu Xing, Jerry L. Prince +4
Tagged magnetic resonance imaging (MRI) is a widely used imaging technique for measuring tissue deformation in moving organs. Due to tagged MRI's intrinsic low anatomical resolutio…
Validating uncertainty in medical image translation
Jacob C. Reinhold, Yufan He, Shizhong Han +5
Medical images are increasingly used as input to deep neural networks to produce quantitative values that aid researchers and clinicians. However, standard deep neural networks do…
Finding novelty with uncertainty
Jacob C. Reinhold, Yufan He, Shizhong Han +5
Medical images are often used to detect and characterize pathology and disease; however, automatically identifying and segmenting pathology in medical images is challenging because…