activity
20182023
most citedReducing Positional Variance in Cross-sectional Abdominal CT Slices with Deep Conditional Generative Models

4 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.QM2023★ 3 cited

Gene-SGAN: a method for discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering

Zhijian Yang, Junhao Wen, Ahmed Abdulkadir +25

Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multipl…

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…

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…

cs.CV2018★ 1 cited

A Novel Extension to Fuzzy Connectivity for Body Composition Analysis: Applications in Thigh, Brain, and Whole Body Tissue Segmentation

Ismail Irmakci, Sarfaraz Hussein, Aydogan Savran +7

Magnetic resonance imaging (MRI) is the non-invasive modality of choice for body tissue composition analysis due to its excellent soft tissue contrast and lack of ionizing radiatio…