activity
20172022
most citedA large annotated medical image dataset for the development and evaluation of segmentation algorithms

718 citations · 934 across the 37 of their papers we have counts for

collaborators

56 papers

eess.IV20224 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…

cs.CV2022

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…

eess.IV20224 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.IV20211 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…

cs.CV20214 cited

Technical Report: Quality Assessment Tool for Machine Learning with Clinical CT

Riqiang Gao, Mirza S. Khan, Yucheng Tang +6

Image Quality Assessment (IQA) is important for scientific inquiry, especially in medical imaging and machine learning. Potential data quality issues can be exacerbated when human-…

eess.IV2021

Lung Cancer Risk Estimation with Incomplete Data: A Joint Missing Imputation Perspective

Riqiang Gao, Yucheng Tang, Kaiwen Xu +7

Data from multi-modality provide complementary information in clinical prediction, but missing data in clinical cohorts limits the number of subjects in multi-modal learning contex…