Search Results for author: Hu Chen

Found 22 papers, 6 papers with code

Depth Completion using Geometry-Aware Embedding

1 code implementation21 Mar 2022 Wenchao Du, Hu Chen, Hongyu Yang, Yi Zhang

The ablation study gives more insights into our method that could achieve significant gains with a simple design, while having better generalization capability and stability.

Depth Completion Depth Estimation

Unsupervised PET Reconstruction from a Bayesian Perspective

no code implementations29 Oct 2021 Chenyu Shen, Wenjun Xia, Hongwei Ye, Mingzheng Hou, Hu Chen, Yan Liu, Jiliu Zhou, Yi Zhang

Positron emission tomography (PET) reconstruction has become an ill-posed inverse problem due to low-count projection data, and a robust algorithm is urgently required to improve imaging quality.

Denoising Image Restoration

A convolutional neural network for teeth margin detection on 3-dimensional dental meshes

no code implementations7 Jul 2021 Hu Chen, Hong Li, Bifu Hu, Kenan Ma, Yuchun Sun

The accuracy, recall and precision were validated on 145 dental meshes to rate the best network structures, which were finally tested on another 144 dental meshes.

One Network to Solve Them All: A Sequential Multi-Task Joint Learning Network Framework for MR Imaging Pipeline

no code implementations14 May 2021 Zhiwen Wang, Wenjun Xia, Zexin Lu, Yongqiang Huang, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang

Magnetic resonance imaging (MRI) acquisition, reconstruction, and segmentation are usually processed independently in the conventional practice of MRI workflow.

IDOL-Net: An Interactive Dual-Domain Parallel Network for CT Metal Artifact Reduction

no code implementations3 Apr 2021 Tao Wang, Wenjun Xia, Zexin Lu, Huaiqiang Sun, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang

Since the dual-domain MAR methods can leverage the hybrid information from both sinogram and image domains, they have significantly improved the performance compared to single-domain methods.

Computed Tomography (CT) Disentanglement +1

PointShuffleNet: Learning Non-Euclidean Features with Homotopy Equivalence and Mutual Information

no code implementations31 Mar 2021 Linchao He, Mengting Luo, Dejun Zhang, Xiao Yang, Hu Chen, Yi Zhang

In this paper, we introduce the homotopy equivalence relation (HER) to make the neural networks learn the data distribution from a high-dimension manifold.

Contrastive Learning Point Cloud Classification

MANAS: Multi-Scale and Multi-Level Neural Architecture Search for Low-Dose CT Denoising

no code implementations24 Mar 2021 Zexin Lu, Wenjun Xia, Yongqiang Huang, Hongming Shan, Hu Chen, Jiliu Zhou, Yi Zhang

Recent advance on neural network architecture search (NAS) has proved that the network architecture has a dramatic effect on the model performance, which indicates that current network architectures for LDCT may be sub-optimal.

Computed Tomography (CT) Denoising +1

ATCSpeechNet: A multilingual end-to-end speech recognition framework for air traffic control systems

no code implementations17 Feb 2021 Yi Lin, Bo Yang, Linchao Li, Dongyue Guo, Jianwei Zhang, Hu Chen, Yi Zhang

Finally, by integrating the SRL with ASR, an end-to-end multilingual ASR framework is formulated in a supervised manner, which is able to translate the raw wave into text in one model, i. e., wave-to-text.

Automatic Speech Recognition Feature Engineering +2

DAN-Net: Dual-Domain Adaptive-Scaling Non-local Network for CT Metal Artifact Reduction

1 code implementation16 Feb 2021 Tao Wang, Wenjun Xia, Yongqiang Huang, Huaiqiang Sun, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang

With the rapid development of deep learning in the field of medical imaging, several network models have been proposed for metal artifact reduction (MAR) in CT.

Computed Tomography (CT) Metal Artifact Reduction

LEARN++: Recurrent Dual-Domain Reconstruction Network for Compressed Sensing CT

1 code implementation13 Dec 2020 Yi Zhang, Hu Chen, Wenjun Xia, Yang Chen, Baodong Liu, Yan Liu, Huaiqiang Sun, Jiliu Zhou

Compressed sensing (CS) computed tomography has been proven to be important for several clinical applications, such as sparse-view computed tomography (CT), digital tomosynthesis and interior tomography.

Computed Tomography (CT) Image Restoration

CT Reconstruction with PDF: Parameter-Dependent Framework for Multiple Scanning Geometries and Dose Levels

no code implementations27 Oct 2020 Wenjun Xia, Zexin Lu, Yongqiang Huang, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang

Current mainstream of CT reconstruction methods based on deep learning usually needs to fix the scanning geometry and dose level, which will significantly aggravate the training cost and need more training data for clinical application.

Fourth-Order Nonlocal Tensor Decomposition Model for Spectral Computed Tomography

no code implementations27 Oct 2020 Xiang Chen, Wenjun Xia, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang

Spectral computed tomography (CT) can reconstruct spectral images from different energy bins using photon counting detectors (PCDs).

Computed Tomography (CT) Image Reconstruction +1

Visual Attention Network for Low Dose CT

no code implementations31 Oct 2018 Wenchao Du, Hu Chen, Peixi Liao, Hongyu Yang, Ge Wang, Yi Zhang

Noise and artifacts are intrinsic to low dose CT (LDCT) data acquisition, and will significantly affect the imaging performance.

Image Restoration

Denoising of 3-D Magnetic Resonance Images Using a Residual Encoder-Decoder Wasserstein Generative Adversarial Network

1 code implementation12 Aug 2018 Maosong Ran, Jinrong Hu, Yang Chen, Hu Chen, Huaiqiang Sun, Jiliu Zhou, Yi Zhang

Structure-preserved denoising of 3D magnetic resonance imaging (MRI) images is a critical step in medical image analysis.

Denoising

LEARN: Learned Experts' Assessment-based Reconstruction Network for Sparse-data CT

no code implementations30 Jul 2017 Hu Chen, Yi Zhang, Yunjin Chen, Junfeng Zhang, Weihua Zhang, Huaiqiaing Sun, Yang Lv, Peixi Liao, Jiliu Zhou, Ge Wang

Compressive sensing (CS) has proved effective for tomographic reconstruction from sparsely collected data or under-sampled measurements, which are practically important for few-view CT, tomosynthesis, interior tomography, and so on.

Compressive Sensing

Effective face landmark localization via single deep network

no code implementations9 Feb 2017 Zongping Deng, Ke Li, Qijun Zhao, Yi Zhang, Hu Chen

In this paper, we propose a novel face alignment method using single deep network (SDN) on existing limited training data.

Data Augmentation Face Alignment

Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)

1 code implementation1 Feb 2017 Hu Chen, Yi Zhang, Mannudeep K. Kalra, Feng Lin, Yang Chen, Peixi Liao, Jiliu Zhou, Ge Wang

Given the potential X-ray radiation risk to the patient, low-dose CT has attracted a considerable interest in the medical imaging field.

Lesion Detection

Low-dose CT denoising with convolutional neural network

no code implementations2 Oct 2016 Hu Chen, Yi Zhang, Weihua Zhang, Peixi Liao, Ke Li, Jiliu Zhou, Ge Wang

To reduce the potential radiation risk, low-dose CT has attracted much attention.

Denoising

Low-Dose CT via Deep Neural Network

no code implementations27 Sep 2016 Hu Chen, Yi Zhang, Weihua Zhang, Peixi Liao, Ke Li, Jiliu Zhou, Ge Wang

In order to reduce the potential radiation risk, low-dose CT has attracted more and more attention.

Medical Physics

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