Search Results for author:
Found 9 papers, 4 papers with code
Pitfalls of defacing whole-head MRI: re-identification risk with diffusion models and compromised research potential
To assess whether the altered voxels in defacing contain universally useful information, we also predict computed tomography (CT)-derived skeletal muscle radiodensity from facial voxels in both defaced and original MRIs.
Robust Body Composition Analysis by Generating 3D CT Volumes from Limited 2D Slices
Body composition analysis provides valuable insights into aging, disease progression, and overall health conditions.
Enhancing Single-Slice Segmentation with 3D-to-2D Unpaired Scan Distillation
2D single-slice abdominal computed tomography (CT) enables the assessment of body habitus and organ health with low radiation exposure.
Deep conditional generative models for longitudinal single-slice abdominal computed tomography harmonization
We further evaluate our method's capability to harmonize longitudinal positional variation on 1033 subjects from the Baltimore Longitudinal Study of Aging (BLSA) dataset, which contains longitudinal single abdominal slices, and confirmed that our method can harmonize the slice positional variance in terms of visceral fat area.
Gene-SGAN: a method for discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering
Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases.
Single Slice Thigh CT Muscle Group Segmentation with Domain Adaptation and Self-Training
The proposed pipeline is effective and robust in extracting muscle groups on 2D single slice CT thigh images. The container is available for public use at https://github. com/MASILab/DA_CT_muscle_seg
Longitudinal Variability Analysis on Low-dose Abdominal CT with Deep Learning-based Segmentation
Metabolic health is increasingly implicated as a risk factor across conditions from cardiology to neurology, and efficiency assessment of body composition is critical to quantitatively characterizing these relationships.
Reducing Positional Variance in Cross-sectional Abdominal CT Slices with Deep Conditional Generative Models
External experiments on 20 subjects from the Baltimore Longitudinal Study of Aging (BLSA) dataset that contains longitudinal single abdominal slices validate that our method can harmonize the slice positional variance in terms of muscle and visceral fat area.
A Novel Extension to Fuzzy Connectivity for Body Composition Analysis: Applications in Thigh, Brain, and Whole Body Tissue Segmentation
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 radiation.
