239 citations · 451 across the 31 of their papers we have counts for
9 papers · 1 filter
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…
3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation
Ho Hin Lee, Shunxing Bao, Yuankai Huo +1
The recent 3D medical ViTs (e.g., SwinUNETR) achieve the state-of-the-art performances on several 3D volumetric data benchmarks, including 3D medical image segmentation. Hierarchic…
Compound Figure Separation of Biomedical Images: Mining Large Datasets for Self-supervised Learning
Tianyuan Yao, Chang Qu, Jun Long +13
With the rapid development of self-supervised learning (e.g., contrastive learning), the importance of having large-scale images (even without annotations) for training a more gene…
Cross-scale Attention Guided Multi-instance Learning for Crohn's Disease Diagnosis with Pathological Images
Ruining Deng, Can Cui, Lucas W. Remedios +12
Multi-instance learning (MIL) is widely used in the computer-aided interpretation of pathological Whole Slide Images (WSIs) to solve the lack of pixel-wise or patch-wise annotation…
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…