4 citations · 28 across the 18 of their papers we have counts for
18 papers
Unsupervised MR-US Multimodal Image Registration with Multilevel Correlation Pyramidal Optimization
Jiazheng Wang, Zeyu Liu, Min Liu +4
Surgical navigation based on multimodal image registration has played a significant role in providing intraoperative guidance to surgeons by showing the relative position of the ta…
Towards Universal Spatial Transcriptomics Super-Resolution: A Generalist Physically Consistent Flow Matching Framework
Xinlei Huang, Weihao Dai, Zijun Qin +5
Spatial transcriptomics provides an unprecedented perspective for deciphering tissue spatial heterogeneity. However, high-resolution spatial transcriptomic technology remains const…
Robust Body Composition Analysis by Generating 3D CT Volumes from Limited 2D Slices
Lianrui Zuo, Xin Yu, Dingjie Su +7
Body composition analysis provides valuable insights into aging, disease progression, and overall health conditions. Due to concerns of radiation exposure, two-dimensional (2D) sin…
Beyond the Lungs: Extending the Field of View in Chest CT with Latent Diffusion Models
Lianrui Zuo, Kaiwen Xu, Dingjie Su +8
The interconnection between the human lungs and other organs, such as the liver and kidneys, is crucial for understanding the underlying risks and effects of lung diseases and impr…
Enhancing Single-Slice Segmentation with 3D-to-2D Unpaired Scan Distillation
Xin Yu, Qi Yang, Han Liu +10
2D single-slice abdominal computed tomography (CT) enables the assessment of body habitus and organ health with low radiation exposure. However, single-slice data necessitates the…
Super-resolution multi-contrast unbiased eye atlases with deep probabilistic refinement
Ho Hin Lee, Adam M. Saunders, Michael E. Kim +15
Purpose: Eye morphology varies significantly across the population, especially for the orbit and optic nerve. These variations limit the feasibility and robustness of generalizing…
DeformUX-Net: Exploring a 3D Foundation Backbone for Medical Image Segmentation with Depthwise Deformable Convolution
Ho Hin Lee, Quan Liu, Qi Yang +4
The application of 3D ViTs to medical image segmentation has seen remarkable strides, somewhat overshadowing the budding advancements in Convolutional Neural Network (CNN)-based mo…
Deep conditional generative models for longitudinal single-slice abdominal computed tomography harmonization
Xin Yu, Qi Yang, Yucheng Tang +8
Two-dimensional single-slice abdominal computed tomography (CT) provides a detailed tissue map with high resolution allowing quantitative characterization of relationships between…
Enhancing Hierarchical Transformers for Whole Brain Segmentation with Intracranial Measurements Integration
Xin Yu, Yucheng Tang, Qi Yang +4
Whole brain segmentation with magnetic resonance imaging (MRI) enables the non-invasive measurement of brain regions, including total intracranial volume (TICV) and posterior fossa…
Multi-Contrast Computed Tomography Atlas of Healthy Pancreas
Yinchi Zhou, Ho Hin Lee, Yucheng Tang +6
With the substantial diversity in population demographics, such as differences in age and body composition, the volumetric morphology of pancreas varies greatly, resulting in disti…
Scaling Up 3D Kernels with Bayesian Frequency Re-parameterization for Medical Image Segmentation
Ho Hin Lee, Quan Liu, Shunxing Bao +7
With the inspiration of vision transformers, the concept of depth-wise convolution revisits to provide a large Effective Receptive Field (ERF) using Large Kernel (LK) sizes for med…
Single Slice Thigh CT Muscle Group Segmentation with Domain Adaptation and Self-Training
Qi Yang, Xin Yu, Ho Hin Lee +8
Objective: Thigh muscle group segmentation is important for assessment of muscle anatomy, metabolic disease and aging. Many efforts have been put into quantifying muscle tissues wi…
Adaptive Contrastive Learning with Dynamic Correlation for Multi-Phase Organ Segmentation
Ho Hin Lee, Yucheng Tang, Han Liu +7
Recent studies have demonstrated the superior performance of introducing ``scan-wise" contrast labels into contrastive learning for multi-organ segmentation on multi-phase computed…
Reducing Positional Variance in Cross-sectional Abdominal CT Slices with Deep Conditional Generative Models
Xin Yu, Qi Yang, Yucheng Tang +8
2D low-dose single-slice abdominal computed tomography (CT) slice enables direct measurements of body composition, which are critical to quantitatively characterizing health relati…
Longitudinal Variability Analysis on Low-dose Abdominal CT with Deep Learning-based Segmentation
Xin Yu, Yucheng Tang, Qi Yang +6
Metabolic health is increasingly implicated as a risk factor across conditions from cardiology to neurology, and efficiency assessment of body composition is critical to quantitati…
UNesT: Local Spatial Representation Learning with Hierarchical Transformer for Efficient Medical Segmentation
Xin Yu, Qi Yang, Yinchi Zhou +12
Transformer-based models, capable of learning better global dependencies, have recently demonstrated exceptional representation learning capabilities in computer vision and medical…
Pseudo-Label Guided Multi-Contrast Generalization for Non-Contrast Organ-Aware Segmentation
Ho Hin Lee, Yucheng Tang, Riqiang Gao +7
Non-contrast computed tomography (NCCT) is commonly acquired for lung cancer screening, assessment of general abdominal pain or suspected renal stones, trauma evaluation, and many…
Characterizing Renal Structures with 3D Block Aggregate Transformers
Xin Yu, Yucheng Tang, Yinchi Zhou +10
Efficiently quantifying renal structures can provide distinct spatial context and facilitate biomarker discovery for kidney morphology. However, the development and evaluation of t…