Kuang Gong

Orcid: 0000-0002-2669-2610

According to our database1, Kuang Gong authored at least 33 papers between 2017 and 2024.

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Bibliography

2024
Anatomically Guided PET Image Reconstruction Using Conditional Weakly-Supervised Multi-Task Learning Integrating Self-Attention.
IEEE Trans. Medical Imaging, June, 2024

Spach Transformer: Spatial and Channel-Wise Transformer Based on Local and Global Self-Attentions for PET Image Denoising.
IEEE Trans. Medical Imaging, June, 2024

Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generation.
CoRR, 2024

Head and Neck Tumor Segmentation from [18F]F-FDG PET/CT Images Based on 3D Diffusion Model.
CoRR, 2024

PET Image Denoising Based on 3D Denoising Diffusion Probabilistic Model: Evaluations on Total-Body Datasets.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

2023
Neural KEM: A Kernel Method With Deep Coefficient Prior for PET Image Reconstruction.
IEEE Trans. Medical Imaging, March, 2023

TauPETGen: Text-Conditional Tau PET Image Synthesis Based on Latent Diffusion Models.
CoRR, 2023

SwinCross: Cross-modal Swin Transformer for Head-and-Neck Tumor Segmentation in PET/CT Images.
CoRR, 2023

2022
Direct Reconstruction of Linear Parametric Images From Dynamic PET Using Nonlocal Deep Image Prior.
IEEE Trans. Medical Imaging, 2022

Penalized-Likelihood PET Image Reconstruction Using 3D Structural Convolutional Sparse Coding.
IEEE Trans. Biomed. Eng., 2022

Unsupervised PET logan parametric image estimation using conditional deep image prior.
Medical Image Anal., 2022

Investigation of Network Architecture for Multimodal Head-and-Neck Tumor Segmentation.
CoRR, 2022

PET image denoising based on denoising diffusion probabilistic models.
CoRR, 2022

A Noise-Level-Aware Framework for PET Image Denoising.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2022

PET Denoising and Uncertainty Estimation Based on NVAE Model Using Quantile Regression Loss.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021
Rapid high-quality PET Patlak parametric image generation based on direct reconstruction and temporal nonlocal neural network.
NeuroImage, 2021

2020
Severity and Consolidation Quantification of COVID-19 From CT Images Using Deep Learning Based on Hybrid Weak Labels.
IEEE J. Biomed. Health Informatics, 2020

Machine Learning in PET: From Photon Detection to Quantitative Image Reconstruction.
Proc. IEEE, 2020

Clinically Translatable Direct Patlak Reconstruction from Dynamic PET with Motion Correction Using Convolutional Neural Network.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Super Resolution of Arterial Spin Labeling MR Imaging Using Unsupervised Multi-scale Generative Adversarial Network.
Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020

2019
Iterative PET Image Reconstruction Using Convolutional Neural Network Representation.
IEEE Trans. Medical Imaging, 2019

PET Image Reconstruction Using Deep Image Prior.
IEEE Trans. Medical Imaging, 2019

Penalized-likelihood PET Image Reconstruction Using 3D Structural Convolutional Sparse Coding.
CoRR, 2019

Consensus Neural Network for Medical Imaging Denoising with Only Noisy Training Samples.
CoRR, 2019

Consensus Neural Network for Medical Imaging Denoising with Only Noisy Training Samples.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Automatic multi-modality segmentation of gross tumor volume for head and neck cancer radiotherapy using 3D U-Net.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019

2018
Penalized PET Reconstruction Using Deep Learning Prior and Local Linear Fitting.
IEEE Trans. Medical Imaging, 2018

Corrections to "Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity".
IEEE Trans. Medical Imaging, 2018

Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity.
IEEE Trans. Medical Imaging, 2018

Learning Personalized Representation for Inverse Problems in Medical Imaging Using Deep Neural Network.
CoRR, 2018

2017
Sinogram Blurring Matrix Estimation From Point Sources Measurements With Rank-One Approximation for Fully 3-D PET.
IEEE Trans. Medical Imaging, 2017

Attenuation Correction for Brain PET imaging using Deep Neural Network based on Dixon and ZTE MR images.
CoRR, 2017

Iterative PET Image Reconstruction Using Convolutional Neural Network Representation.
CoRR, 2017


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