Thomas Z. Li
Orcid: 0000-0001-9950-4679
According to our database1,
Thomas Z. Li
authored at least 18 papers
between 2022 and 2025.
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Bibliography
2025
Multipath cycleGAN for harmonization of paired and unpaired low-dose lung computed tomography reconstruction kernels.
CoRR, May, 2025
Beyond the Lungs: Extending the Field of View in Chest CT with Latent Diffusion Models.
CoRR, January, 2025
Unsupervised discovery of clinical disease signatures using probabilistic independence.
J. Biomed. Informatics, 2025
CT Contrast Phase Identification by Predicting the Temporal Angle Using Circular Regression.
Proceedings of the 22nd IEEE International Symposium on Biomedical Imaging, 2025
2024
Data-driven Nucleus Subclassification on Colon H&E using Style-transferred Digital Pathology.
CoRR, 2024
Unsupervised Discovery of Clinical Disease Signatures Using Probabilistic Independence.
CoRR, 2024
2023
UNesT: Local spatial representation learning with hierarchical transformer for efficient medical segmentation.
Medical Image Anal., December, 2023
Body composition assessment with limited field-of-view computed tomography: A semantic image extension perspective.
Medical Image Anal., August, 2023
Inter-vendor harmonization of Computed Tomography (CT) reconstruction kernels using unpaired image translation.
CoRR, 2023
CoRR, 2023
Proceedings of the Medical Imaging 2023: Image Processing, 2023
Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography.
Proceedings of the Medical Imaging 2023: Image Processing, 2023
Longitudinal Multimodal Transformer Integrating Imaging and Latent Clinical Signatures from Routine EHRs for Pulmonary Nodule Classification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Scaling up 3D Kernels with Bayesian Frequency Re-parameterization for Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
2022
A Comparative Study of Confidence Calibration in Deep Learning: From Computer Vision to Medical Imaging.
CoRR, 2022
Reducing uncertainty in cancer risk estimation for patients with indeterminate pulmonary nodules using an integrated deep learning model.
Comput. Biol. Medicine, 2022