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20202025
most citedFederated Learning Enables Big Data for Rare Cancer Boundary Detection

390 citations · 403 across the 19 of their papers we have counts for

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13 papers · 1 filter

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…

eess.IV2025

Pitfalls of defacing whole-head MRI: re-identification risk with diffusion models and compromised research potential

Chenyu Gao, Kaiwen Xu, Michael E. Kim +11

Defacing is often applied to head magnetic resonance image (MRI) datasets prior to public release to address privacy concerns. The alteration of facial and nearby voxels has provok…

eess.IV2023

Inter-vendor harmonization of Computed Tomography (CT) reconstruction kernels using unpaired image translation

Aravind R. Krishnan, Kaiwen Xu, Thomas Li +9

The reconstruction kernel in computed tomography (CT) generation determines the texture of the image. Consistency in reconstruction kernels is important as the underlying CT textur…

eess.IV2023

Zero-shot CT Field-of-view Completion with Unconditional Generative Diffusion Prior

Kaiwen Xu, Aravind R. Krishnan, Thomas Z. Li +4

Anatomically consistent field-of-view (FOV) completion to recover truncated body sections has important applications in quantitative analyses of computed tomography (CT) with limit…

eess.IV2023

Longitudinal Multimodal Transformer Integrating Imaging and Latent Clinical Signatures From Routine EHRs for Pulmonary Nodule Classification

Thomas Z. Li, John M. Still, Kaiwen Xu +11

The accuracy of predictive models for solitary pulmonary nodule (SPN) diagnosis can be greatly increased by incorporating repeat imaging and medical context, such as electronic hea…

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★ 1 cited

Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography

Thomas Z. Li, Kaiwen Xu, Riqiang Gao +5

Features learned from single radiologic images are unable to provide information about whether and how much a lesion may be changing over time. Time-dependent features computed fro…

eess.IV2022★ 1 cited

Body Composition Assessment with Limited Field-of-view Computed Tomography: A Semantic Image Extension Perspective

Kaiwen Xu, Thomas Li, Mirza S. Khan +6

Field-of-view (FOV) tissue truncation beyond the lungs is common in routine lung screening computed tomography (CT). This poses limitations for opportunistic CT- based body composi…

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…

eess.IV2020★ 1 cited

Multi-Contrast Computed Tomography Healthy Kidney Atlas

Ho Hin Lee, Yucheng Tang, Kaiwen Xu +8

The construction of three-dimensional multi-modal tissue maps provides an opportunity to spur interdisciplinary innovations across temporal and spatial scales through information i…

eess.IV2020

Development and Characterization of a Chest CT Atlas

Kaiwen Xu, Riqiang Gao, Mirza S. Khan +8

A major goal of lung cancer screening is to identify individuals with particular phenotypes that are associated with high risk of cancer. Identifying relevant phenotypes is complic…

eess.IV2020

Deep Multi-path Network Integrating Incomplete Biomarker and Chest CT Data for Evaluating Lung Cancer Risk

Riqiang Gao, Yucheng Tang, Kaiwen Xu +7

Clinical data elements (CDEs) (e.g., age, smoking history), blood markers and chest computed tomography (CT) structural features have been regarded as effective means for assessing…