collaborators

6 papers

cs.CV2025

Self-supervised learning of imaging and clinical signatures using a multimodal joint-embedding predictive architecture

Thomas Z. Li, Aravind R. Krishnan, Lianrui Zuo +5

The development of multimodal models for pulmonary nodule diagnosis is limited by the scarcity of labeled data and the tendency for these models to overfit on the training distribu…

cs.LG2025

Cohort-Aware Agents for Individualized Lung Cancer Risk Prediction Using a Retrieval-Augmented Model Selection Framework

Chongyu Qu, Allen J. Luna, Thomas Z. Li +6

Accurate lung cancer risk prediction remains challenging due to substantial variability across patient populations and clinical settings -- no single model performs best for all co…

eess.IV2025

Multipath cycleGAN for harmonization of paired and unpaired low-dose lung computed tomography reconstruction kernels

Aravind R. Krishnan, Thomas Z. Li, Lucas W. Remedios +12

Reconstruction kernels in computed tomography (CT) affect spatial resolution and noise characteristics, introducing systematic variability in quantitative imaging measurements such…

eess.IV2025

Investigating the impact of kernel harmonization and deformable registration on inspiratory and expiratory chest CT images for people with COPD

Aravind R. Krishnan, Yihao Liu, Kaiwen Xu +9

Paired inspiratory-expiratory CT scans enable the quantification of gas trapping due to small airway disease and emphysema by analyzing lung tissue motion in COPD patients. Deforma…

cs.CV2025

Robust Body Composition Analysis by Generating 3D CT Volumes from Limited 2D Slices

Lianrui Zuo, Xin Yu, Dingjie Su +7

Body composition analysis provides valuable insights into aging, disease progression, and overall health conditions. Due to concerns of radiation exposure, two-dimensional (2D) sin…

cs.CV2025

Beyond the Lungs: Extending the Field of View in Chest CT with Latent Diffusion Models

Lianrui Zuo, Kaiwen Xu, Dingjie Su +8

The interconnection between the human lungs and other organs, such as the liver and kidneys, is crucial for understanding the underlying risks and effects of lung diseases and impr…