no code implementations • 14 Apr 2023 • Chunyan Xiong, Mengli Lu, Xiaotong Yu, Jian Cao, Zhong Chen, Di Guo, Xiaobo Qu
Soft-thresholding has been widely used in neural networks.
no code implementations • 29 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.
no code implementations • 4 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).
no code implementations • 2 Dec 2022 • Tianyu Qiu, Amir Jahangiri, Xiao Han, Dmitry Lesovoy, Tatiana Agback, Peter Agback, Adnane Achour, Xiaobo Qu, Vladislav Orekhov
Nuclear magnetic resonance (NMR) spectroscopy has become a formidable tool for biochemistry and medicine.
no code implementations • 24 Nov 2022 • Yihui Huang, Zi Wang, Xinlin Zhang, Jian Cao, Zhangren Tu, Di Guo, Xiaobo Qu
Recently, the low rankness of these exponentials has been applied to implicitly constrain the deep learning network through the unrolling of low rank Hankel factorization algorithm.
no code implementations • 23 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.
no code implementations • 20 Oct 2022 • Chen Qian, Zi Wang, Xinlin Zhang, Qingrui Cai, Taishan Kang, Boyu Jiang, Ran Tao, Zhigang Wu, Di Guo, Xiaobo Qu
In this work, we propose a Physics-Informed Deep Diffusion magnetic resonance imaging (DWI) reconstruction method (PIDD).
1 code implementation • 30 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.
no code implementations • 28 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.
no code implementations • 21 Mar 2022 • Qinqin Yang, Zi Wang, Kunyuan Guo, Congbo Cai, Xiaobo Qu
Deep learning has innovated the field of computational imaging.
no code implementations • 18 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.
no code implementations • 9 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).
no code implementations • 4 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.
no code implementations • 24 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.
no code implementations • 18 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).
no code implementations • 26 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).
1 code implementation • 29 Dec 2020 • Zi Wang, Di Guo, Zhangren Tu, Yihui Huang, Yirong Zhou, Jian Wang, Liubin Feng, Donghai Lin, Yongfu You, Tatiana Agback, Vladislav Orekhov, Xiaobo Qu
The non-uniform sampling is a powerful approach to enable fast acquisition but requires sophisticated reconstruction algorithms.
no code implementations • 13 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.
no code implementations • 10 Sep 2020 • Yongzhi Zhang, Xiaobo Qu, Lang Tong
In this real time control model, a novel state-space model is first developed to capture vehicle speed, acceleration, and state of charge.
no code implementations • 13 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.
no code implementations • 13 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.
no code implementations • 24 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.
no code implementations • 17 Sep 2019 • Xinlin Zhang, Hengfa Lu, Di Guo, Lijun Bao, Feng Huang, Qin Xu, Xiaobo Qu
The pFISTA, a simple and efficient algorithm for sparse reconstruction, has been successfully extended to parallel imaging.
no code implementations • 9 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.
no code implementations • 6 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.
no code implementations • 29 Apr 2015 • Yunsong Liu, Zhifang Zhan, Jian-Feng Cai, Di Guo, Zhong Chen, Xiaobo Qu
It has been shown that, redundant image representations, e. g. tight frames, can significantly improve the image quality.
no code implementations • 10 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.
no code implementations • 10 Mar 2015 • Zhifang Zhan, Jian-Feng Cai, Di Guo, Yunsong Liu, Zhong Chen, Xiaobo Qu
The proposed method is compared with state-of-the-art magnetic resonance image reconstruction methods.