390 citations · 403 across the 19 of their papers we have counts for
19 papers
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…
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…
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…
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…
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…
No winners: Performance of lung cancer prediction models depends on screening-detected, incidental, and biopsied pulmonary nodule use cases
Thomas Z. Li, Kaiwen Xu, Aravind Krishnan +14
Statistical models for predicting lung cancer have the potential to facilitate earlier diagnosis of malignancy and avoid invasive workup of benign disease. Many models have been pu…
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…
Statistically Significant Concept-based Explanation of Image Classifiers via Model Knockoffs
Kaiwen Xu, Kazuto Fukuchi, Youhei Akimoto +1
A concept-based classifier can explain the decision process of a deep learning model by human-understandable concepts in image classification problems. However, sometimes concept-b…
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…
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…
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…
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…
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…
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Sarthak Pati, Ujjwal Baid, Brandon Edwards +276
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…
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-…
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…
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…
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…
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…