Junchi Liu

According to our database, Junchi Liu authored at least 17 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

TransConv: Transformer Meets Contextual Convolution for Unsupervised Domain Adaptation.

Junchi Liu, Xiang Zhang, Zhigang Luo

Entropy, June, 2024

Atmospheric Light Estimation Using Polarization Degree Gradient for Image Dehazing.

Shuai Liu, Hang Li, Jinyu Zhao, Junchi Liu, Youqiang Zhu, Zhenduo Zhang

Sensors, May, 2024

2023

Restoration of Spatially Variant Blurred Images with Wide-Field Telescope Based on Deep Learning.

Yingmei Tian, Jianli Wang, Junchi Liu, Xiangji Guo

Sensors, April, 2023

Nonuniform Correction of Ground-Based Optical Telescope Image Based on Conditional Generative Adversarial Network.

Xiangji Guo, Tao Chen, Junchi Liu, Yuan Liu, Qichang An, Chunfeng Jiang

Sensors, February, 2023

2022

Dim Space Target Detection via Convolutional Neural Network in Single Optical Image.

Xiangji Guo, Tao Chen, Junchi Liu, Yuan Liu, Qichang An

IEEE Access, 2022

Dose-Blind Denoising With Deep Learning in Cardiac Spect.

Junchi Liu, Yongyi Yang, Miles N. Wernick, P. Hendrik Pretorius, Michael A. King

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021

Improving Diagnostic Accuracy Of Reduced-Dose Studies With Full-Dose Noise-To-Noise Learning In Cardiac Spect.

Junchi Liu, Yongyi Yang, Miles N. Wernick, P. Hendrik Pretorius, Michael A. King

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Accounting For Inter-Subject Variations in Deep Learning for Reduced-Dose Studies in Cardiac SPECT.

Junchi Liu, Yongyi Yang, Miles N. Wernick, P. Hendrik Pretorius, Michael A. King

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

PageRank Centrality based Graph Convolutional Networks for Semi-supervised Node Classification.

Lei Chen, Junchi Liu, Xueyuan Zhang, Qifeng Zhou

Proceedings of the 16th International Conference on Computer Science & Education, 2021

2020

Artifact reduction in brain magnetic resonance imaging (MRI) by means of a dense residual network with K-space blending (DRN-KB).

Junchi Liu, Jie Deng

Proceedings of the Medical Imaging 2020: Image Processing, 2020

2018

Mixed L₁ norm and L₂ norm regularized sparsity adaptive matching pursuit algorithm.

Nian Cai, Qian Ye, Jing Wang, Guandong Cen, Junchi Liu, Han Wang, Bingo Wing-Kuen Ling

Signal Image Video Process., 2018

Mixture of Deep-Learning Experts for Separation of Bones from Soft Tissue in Chest Radiographs.

Amin Zarshenas, Junchi Liu, Paul Forti, Kenji Suzuki

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018

Radiation dose reduction in digital breast tomosynthesis (DBT) by means of deep-learning-based supervised image processing.

Junchi Liu, Amin Zarshenas, Ammar Qadir, Zheng Wei, Limin Yang, Laurie Lee Fajardo, Kenji Suzuki

Proceedings of the Medical Imaging 2018: Image Processing, 2018

Deep neural network convolution (NNC) for three-class classification of diffuse lung disease opacities in high-resolution CT (HRCT): Consolidation, ground-glass opacity (GGO), and normal opacity.

Noriaki Hashimoto, Kenji Suzuki, Junchi Liu, Yasushi Hirano, Heber MacMahon, Shoji Kido

Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

Radiation dose reduction in digital breast tomosynthesis (DBT) by means of neural network convolution (NNC) deep learning.

Junchi Liu, Amin Zarshenas, Syed Ammar Qadir, Limin Yang, Laurie Lee Fajardo, Kenji Suzuki

Proceedings of the 14th International Workshop on Breast Imaging, 2018

2017

Neural Network Convolution (NNC) for Converting Ultra-Low-Dose to "Virtual" High-Dose CT Images.

Kenji Suzuki, Junchi Liu, Amin Zarshenas, Toru Higaki, Wataru Fukumoto, Kazuo Awai

Proceedings of the Machine Learning in Medical Imaging - 8th International Workshop, 2017

2015

Development of Computer-Aided Diagnostic (CADx) System for Distinguishing Neoplastic from Nonneoplastic Lesions in CT Colonography (CTC): Toward CTC beyond Detection.

Kenji Suzuki, Mohammadamin Zarshenas, Junchi Liu, Yonghui Fan, Nazanin Makkinejad, Paul Forti, Abraham H. Dachman

Proceedings of the 2015 IEEE International Conference on Systems, 2015