Search Results for author: Xiaobo Qu

Found 39 papers, 4 papers with code

Robust recovery of complex exponential signals from random Gaussian projections via low rank Hankel matrix reconstruction

no code implementations10 Mar 2015 Jian-Feng Cai, Xiaobo Qu, Weiyu Xu, Gui-Bo Ye

Our method can be applied to spectral compressed sensing where the signal of interest is a superposition of $R$ complex sinusoids.

Hankel Matrix Nuclear Norm Regularized Tensor Completion for $N$-dimensional Exponential Signals

no code implementations6 Apr 2016 Jiaxi Ying, Hengfa Lu, Qingtao Wei, Jian-Feng Cai, Di Guo, Jihui Wu, Zhong Chen, Xiaobo Qu

Signals are generally modeled as a superposition of exponential functions in spectroscopy of chemistry, biology and medical imaging.

Accelerated Nuclear Magnetic Resonance Spectroscopy with Deep Learning

no code implementations9 Apr 2019 Xiaobo Qu, Yihui Huang, Hengfa Lu, Tianyu Qiu, Di Guo, Tatiana Agback, Vladislav Orekhov, Zhong Chen

Nuclear magnetic resonance (NMR) spectroscopy serves as an indispensable tool in chemistry and biology but often suffers from long experimental time.

pISTA-SENSE-ResNet for Parallel MRI Reconstruction

no code implementations24 Sep 2019 Tieyuan Lu, Xinlin Zhang, Yihui Huang, Yonggui Yang, Gang Guo, Lijun Bao, Feng Huang, Di Guo, Xiaobo Qu

Magnetic resonance imaging has been widely applied in clinical diagnosis, however, is limited by its long data acquisition time.

MRI Reconstruction

Review and Prospect: Deep Learning in Nuclear Magnetic Resonance Spectroscopy

no code implementations13 Jan 2020 Dicheng Chen, Zi Wang, Di Guo, Vladislav Orekhov, Xiaobo Qu

In this Minireview, we summarize applications of DL in Nuclear Magnetic Resonance (NMR) spectroscopy and outline a perspective for DL as entirely new approaches that are likely to transform NMR spectroscopy into a much more efficient and powerful technique in chemistry and life science.

Exponential Signal Reconstruction with Deep Hankel Matrix Factorization

no code implementations13 Jul 2020 Yihui Huang, Jinkui Zhao, Zi Wang, Vladislav Orekhov, Di Guo, Xiaobo Qu

Exponential is a basic signal form, and how to fast acquire this signal is one of the fundamental problems and frontiers in signal processing.

Rolling Shutter Correction

TLab: Traffic Map Movie Forecasting Based on HR-NET

no code implementations13 Nov 2020 Fanyou Wu, Yang Liu, Zhiyuan Liu, Xiaobo Qu, Rado Gazo, Eva Haviarova

In our 2020 Competition solution, we further design multiple variants based on HR-NET and UNet.

Feature Engineering

Magnetic Resonance Spectroscopy Deep Learning Denoising Using Few In Vivo Data

no code implementations26 Jan 2021 Dicheng Chen, Wanqi Hu, Huiting Liu, Yirong Zhou, Tianyu Qiu, Yihui Huang, Zi Wang, Jiazheng Wang, Liangjie Lin, Zhigang Wu, Hao Chen, Xi Chen, Gen Yan, Di Guo, Jianzhong Lin, Xiaobo Qu

A deep learning model, Refusion Long Short-Term Memory (ReLSTM), was designed to learn the mapping from the low SNR time-domain data (24 SA) to the high SNR one (128 SA).

Denoising

XCloud-pFISTA: A Medical Intelligence Cloud for Accelerated MRI

no code implementations18 Apr 2021 Yirong Zhou, Chen Qian, Yi Guo, Zi Wang, Jian Wang, Biao Qu, Di Guo, Yongfu You, Xiaobo Qu

Machine learning and artificial intelligence have shown remarkable performance in accelerated magnetic resonance imaging (MRI).

Cloud Computing Image Reconstruction

Accelerated MRI Reconstruction with Separable and Enhanced Low-Rank Hankel Regularization

no code implementations24 Jul 2021 Xinlin Zhang, Hengfa Lu, Di Guo, Zongying Lai, Huihui Ye, Xi Peng, Bo Zhao, Xiaobo Qu

The combination of the sparse sampling and the low-rank structured matrix reconstruction has shown promising performance, enabling a significant reduction of the magnetic resonance imaging data acquisition time.

MRI Reconstruction

Improving Freeway Merging Efficiency via Flow-Level Coordination of Connected and Autonomous Vehicles

no code implementations4 Aug 2021 Jie Zhu, Ivana Tasic, Xiaobo Qu

Freeway on-ramps are typical bottlenecks in the freeway network due to the frequent disturbances caused by their associated merging, weaving, and lane-changing behaviors.

Autonomous Vehicles

One-dimensional Deep Low-rank and Sparse Network for Accelerated MRI

no code implementations9 Dec 2021 Zi Wang, Chen Qian, Di Guo, Hongwei Sun, Rushuai Li, Bo Zhao, Xiaobo Qu

Deep learning has shown astonishing performance in accelerated magnetic resonance imaging (MRI).

Flow-level Coordination of Connected and Autonomous Vehicles in Multilane Freeway Ramp Merging Areas

no code implementations18 Feb 2022 Jie Zhu, Ivana Tasic, Xiaobo Qu

The strategy is formulated under an optimization framework, where the optimal control plan is determined based on real-time traffic conditions.

Autonomous Vehicles

A Paired Phase and Magnitude Reconstruction for Advanced Diffusion-Weighted Imaging

no code implementations28 Mar 2022 Chen Qian, Zi Wang, Xinlin Zhang, Boxuan Shi, Boyu Jiang, Ran Tao, Jing Li, Yuwei Ge, Taishan Kang, Jianzhong Lin, Di Guo, Xiaobo Qu

Conclusion: The explicit phase model PAIR with complementary priors has a good performance on challenging reconstructions under inter-shot motions between shots and a low signal-to-noise ratio.

Some Practice for Improving the Search Results of E-commerce

1 code implementation30 Jul 2022 Fanyou Wu, Yang Liu, Rado Gazo, Benes Bedrich, Xiaobo Qu

In the Amazon KDD Cup 2022, we aim to apply natural language processing methods to improve the quality of search results that can significantly enhance user experience and engagement with search engines for e-commerce.

A Faithful Deep Sensitivity Estimation for Accelerated Magnetic Resonance Imaging

no code implementations23 Oct 2022 Zi Wang, Haoming Fang, Chen Qian, Boxuan Shi, Lijun Bao, Liuhong Zhu, Jianjun Zhou, Wenping Wei, Jianzhong Lin, Di Guo, Xiaobo Qu

To understand the behavior of the network, the mutual promotion of sensitivity estimation and image reconstruction is revealed through the visualization of network intermediate results.

MRI Reconstruction

CloudBrain-ReconAI: An Online Platform for MRI Reconstruction and Image Quality Evaluation

no code implementations4 Dec 2022 Yirong Zhou, Chen Qian, Jiayu Li, Zi Wang, Yu Hu, Biao Qu, Liuhong Zhu, Jianjun Zhou, Taishan Kang, Jianzhong Lin, Qing Hong, Jiyang Dong, Di Guo, Xiaobo Qu

Efficient collaboration between engineers and radiologists is important for image reconstruction algorithm development and image quality evaluation in magnetic resonance imaging (MRI).

Cloud Computing MRI Reconstruction

A Dynamics Theory of Implicit Regularization in Deep Low-Rank Matrix Factorization

no code implementations29 Dec 2022 Jian Cao, Chen Qian, Yihui Huang, Dicheng Chen, Yuncheng Gao, Jiyang Dong, Di Guo, Xiaobo Qu

Recent theory starts to explain implicit regularization with the model of deep matrix factorization (DMF) and analyze the trajectory of discrete gradient dynamics in the optimization process.

One for Multiple: Physics-informed Synthetic Data Boosts Generalizable Deep Learning for Fast MRI Reconstruction

1 code implementation25 Jul 2023 Zi Wang, Xiaotong Yu, Chengyan Wang, Weibo Chen, Jiazheng Wang, Ying-Hua Chu, Hongwei Sun, Rushuai Li, Peiyong Li, Fan Yang, Haiwei Han, Taishan Kang, Jianzhong Lin, Chen Yang, Shufu Chang, Zhang Shi, Sha Hua, Yan Li, Juan Hu, Liuhong Zhu, Jianjun Zhou, Meijing Lin, Jiefeng Guo, Congbo Cai, Zhong Chen, Di Guo, Guang Yang, Xiaobo Qu

We demonstrate that training DL models on synthetic data, coupled with enhanced learning techniques, yields in vivo MRI reconstructions comparable to or surpassing those of models trained on matched realistic datasets, reducing the reliance on real-world MRI data by up to 96%.

Medical Diagnosis MRI Reconstruction

A plug-and-play synthetic data deep learning for undersampled magnetic resonance image reconstruction

no code implementations13 Sep 2023 Min Xiao, Zi Wang, Jiefeng Guo, Xiaobo Qu

Magnetic resonance imaging (MRI) plays an important role in modern medical diagnostic but suffers from prolonged scan time.

De-aliasing MRI Reconstruction

Bloch Equation Enables Physics-informed Neural Network in Parametric Magnetic Resonance Imaging

no code implementations21 Sep 2023 Qingrui Cai, Liuhong Zhu, Jianjun Zhou, Chen Qian, Di Guo, Xiaobo Qu

PINN enables learning the Bloch equation, estimating the T2 parameter, and generating a series of physically synthetic data.

Network Interpretation

Cloud-Magnetic Resonance Imaging System: In the Era of 6G and Artificial Intelligence

no code implementations18 Oct 2023 Yirong Zhou, Yanhuang Wu, Yuhan Su, Jing Li, Jianyun Cai, Yongfu You, Di Guo, Xiaobo Qu

The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data (ISMRMRD) format.

Cloud Computing Edge-computing +3

NMR Spectra Denoising with Vandermonde Constraints

no code implementations21 Oct 2023 Di Guo, Runmin Xu, Jinyu Wu, Meijin Lin, Xiaofeng Du, Xiaobo Qu

Nuclear magnetic resonance (NMR) spectroscopy serves as an important tool to analyze chemicals and proteins in bioengineering.

Denoising

Quantitative Analysis of Molecular Transport in the Extracellular Space Using Physics-Informed Neural Network

no code implementations23 Jan 2024 Jiayi Xie, Hongfeng Li, Jin Cheng, Qingrui Cai, Hanbo Tan, Lingyun Zu, Xiaobo Qu, Hongbin Han

Consequently, the proposed method allows for the quantitative analysis and identification of the specific pattern of molecular transport within the ECS through the calculation of the Peclet number.

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