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20172023
most cited3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation

103 citations · 196 across the 24 of their papers we have counts for

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9 papers · 1 filter

eess.IV2022★ 1 cited

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…

eess.IV2022★ 4 cited

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…

eess.IV2022★ 4 cited

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…

eess.IV2022★ 4 cited

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…

eess.IV2021★ 1 cited

Random Multi-Channel Image Synthesis for Multiplexed Immunofluorescence Imaging

Shunxing Bao, Yucheng Tang, Ho Hin Lee +8

Multiplex immunofluorescence (MxIF) is an emerging imaging technique that produces the high sensitivity and specificity of single-cell mapping. With a tenet of 'seeing is believing…

eess.IV2020

RAP-Net: Coarse-to-Fine Multi-Organ Segmentation with Single Random Anatomical Prior

Ho Hin Lee, Yucheng Tang, Shunxing Bao +3

Performing coarse-to-fine abdominal multi-organ segmentation facilitates to extract high-resolution segmentation minimizing the lost of spatial contextual information. However, cur…