Search Results for author: Kuang Gong

Found 8 papers, 1 papers with code

Direct Reconstruction of Linear Parametric Images from Dynamic PET Using Nonlocal Deep Image Prior

no code implementations18 Jun 2021 Kuang Gong, Ciprian Catana, Jinyi Qi, Quanzheng Li

Direct reconstruction methods have been developed to estimate parametric images directly from the measured PET sinograms by combining the PET imaging model and tracer kinetics in an integrated framework.

Denoising

Super Resolution of Arterial Spin Labeling MR Imaging Using Unsupervised Multi-Scale Generative Adversarial Network

no code implementations14 Sep 2020 Jianan Cui, Kuang Gong, Paul Han, Huafeng Liu, Quanzheng Li

After the network was trained, the super-resolution (SR) image was generated by supplying the upsampled LR ASL image and corresponding T1-weighted image to the generator of the last layer.

SSIM Super-Resolution

Clinically Translatable Direct Patlak Reconstruction from Dynamic PET with Motion Correction Using Convolutional Neural Network

no code implementations13 Sep 2020 Nuobei Xie, Kuang Gong, Ning Guo, Zhixing Qin, Jianan Cui, Zhifang Wu, Huafeng Liu, Quanzheng Li

Patlak model is widely used in 18F-FDG dynamic positron emission tomography (PET) imaging, where the estimated parametric images reveal important biochemical and physiology information.

Denoising

Consensus Neural Network for Medical Imaging Denoising with Only Noisy Training Samples

no code implementations9 Jun 2019 Dufan Wu, Kuang Gong, Kyungsang Kim, Quanzheng Li

In this paper we proposed a training method which learned denoising neural networks from noisy training samples only.

Image Denoising Medical Image Denoising

Attenuation correction for brain PET imaging using deep neural network based on dixon and ZTE MR images

no code implementations17 Dec 2017 Kuang Gong, Jaewon Yang, Kyungsang Kim, Georges El Fakhri, Youngho Seo, Quanzheng Li

With only Dixon MR images as the network input, the existing U-net structure was adopted and analysis using forty patient data sets shows it is superior than other Dixon based methods.

Image Reconstruction

Iterative PET Image Reconstruction Using Convolutional Neural Network Representation

1 code implementation9 Oct 2017 Kuang Gong, Jiahui Guan, Kyungsang Kim, Xuezhu Zhang, Georges El Fakhri, Jinyi Qi, Quanzheng Li

An innovative feature of the proposed method is that we embed the neural network in the iterative reconstruction framework for image representation, rather than using it as a post-processing tool.

Denoising Image Reconstruction

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