David S. Yu

Orcid: 0000-0002-2781-5379

According to our database1, David S. Yu authored at least 15 papers between 2019 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
OpenVocabCT: Toward Universal Text-Driven CT Image Segmentation.
IEEE Trans. Medical Imaging, May, 2026

Vision foundation model for 3D magnetic resonance imaging segmentation, classification, and registration.
Medical Image Anal., 2026

2025
An Efficient 3D Latent Diffusion Model for T1-contrast Enhanced MRI Generation.
CoRR, September, 2025

Generalizable 7T T1-map Synthesis from 1.5T and 3T T1 MRI with an Efficient Transformer Model.
CoRR, July, 2025

Unifying Biomedical Vision-Language Expertise: Towards a Generalist Foundation Model via Multi-CLIP Knowledge Distillation.
CoRR, June, 2025

Towards Universal Text-driven CT Image Segmentation.
CoRR, March, 2025

MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shifting.
CoRR, March, 2025

Triad: Vision Foundation Model for 3D Magnetic Resonance Imaging.
CoRR, February, 2025

A Physics-Informed Deep Learning Model for MRI Brain Motion Correction.
CoRR, February, 2025

2024
T1-contrast Enhanced MRI Generation from Multi-parametric MRI for Glioma Patients with Latent Tumor Conditioning.
CoRR, 2024

2023
Synthetic CT Generation from MRI using 3D Transformer-based Denoising Diffusion Model.
CoRR, 2023

2022
Automated CT segmentation for rapid assessment of anatomical variations in head-and-neck radiation therapy.
Proceedings of the Medical Imaging 2022: Image-Guided Procedures, 2022

2020
Organ-at-Risk (OAR) segmentation in head and neck CT using U-RCNN.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

Synthetic CT-aided MRI-CT image registration for head and neck radiotherapy.
Proceedings of the Medical Imaging 2020: Biomedical Applications in Molecular, 2020

2019
Automatic multi-organ segmentation in thorax CT images using U-Net-GAN.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019


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