Deep Convolutional Neural Network for Inverse Problems in Imaging

Cited by (1,000)

Items 301–400 of 1,000

1. Consensus Neural Network for Medical Imaging Denoising with Only Noisy Training Samples
   Dufan Wu, Kuang Gong, Kyungsang Kim, Xiang Li, Quanzheng Li · 2019 · Lecture notes in computer science
2. Improved Low-Count Quantitative PET Reconstruction With an Iterative Neural Network
   Hongki Lim, Il Yong Chun, Yuni K. Dewaraja · 2020 · IEEE Transactions on Medical Imaging
3. Limited View Tomographic Reconstruction Using a Cascaded Residual Dense Spatial-Channel Attention Network With Projection Data Fidelity Layer
   Bo Zhou, S. Kevin Zhou, James S. Duncan, Chi Liu · 2021 · IEEE Transactions on Medical Imaging
4. Multi-Object Detection in Traffic Scenes Based on Improved SSD
   Xinqing Wang, Xia Hua, Feng Xiao, Yuyang Li, Xiaodong Hu, Pengyu Sun · 2018 · Electronics
5. PhUn-Net: ready-to-use neural network for unwrapping quantitative phase images of biological cells
   Gili Dardikman-Yoffe, Darina Roitshtain, Simcha K. Mirsky · 2020 · Biomedical Optics Express
6. Chest X-ray Bone Suppression for Improving Classification of Tuberculosis-Consistent Findings
   Sivaramakrishnan Rajaraman, Ghada Zamzmi, Les Roger Folio, Philip O. Alderson, Sameer Antani · 2021 · Diagnostics
7. Quantitative Susceptibility Mapping: Technical Considerations and Clinical Applications in Neuroimaging
   Selvadasan Vinayagamani, R Sheelakumari, Sekar Sabarish, Santhakumar Senthilvelan, Roopa Ros, Bejoy Thomas, Chandrasekharan Kesavadas · 2020 · Journal of Magnetic Resonance Imaging
8. The troublesome kernel: why deep learning for inverse problems is typically unstable.
   Nina Maria Gottschling, Vegard Antun, Ben Adcock, Anders C. Hansen · 2020 · arXiv (Cornell University)
9. Convolutional Neural Network-Based Robust Denoising of Low-Dose Computed Tomography Perfusion Maps
   Venkata S. Kadimesetty, Sreedevi Gutta, Sriram Ganapathy, Phaneendra Kumar Yalavarthy · 2018 · IEEE Transactions on Radiation and Plasma Medical Sciences
10. Dual-domain cascade of U-nets for multi-channel magnetic resonance image reconstruction
    Roberto Medeiros de Souza, Mariana Bento, Nikita Nogovitsyn, Kevin J. Chung, Wallace Loos, Robert Marc Lebel, Richard Frayne · 2020 · Magnetic Resonance Imaging
11. Untrained networks for compressive lensless photography
    Kristina Monakhova, Vi Tran, Grace Kuo, Laura Waller · 2021 · Optics Express
12. GCN-Denoiser: Mesh Denoising with Graph Convolutional Networks
    Yuefan Shen, Hongbo Fu, Zhongshuo Du, Xiang Chen, Evgeny Vladimirovich Burnaev, Denis Zorin, Kun Zhou, Youyi Zheng · 2022 · ACM Transactions on Graphics
13. Learning-Rate Annealing Methods for Deep Neural Networks
    Kensuke Nakamura, Bilel Derbel, Kyoung‐Jae Won, Byung‐Woo Hong · 2021 · Electronics
14. Deep Learning for Passive Synthetic Aperture Radar
    Yonel, Bariscan, Mason, Eric, Yazici, Birsen · 2018 · IEEE Journal of Selected Topics in Signal Processing
15. Scatter correction of cone-beam CT using a deep residual convolution neural network (DRCNN)
    Yangkang Jiang, Chunlin Yang, Pengfei Yang et al. · 2019 · Physics in Medicine and Biology
16. Focusing light through scattering media by reinforced hybrid algorithms
    Yunqi Luo, Suxia Yan, Huanhao Li · 2020 · APL Photonics
17. Artifact removal using a hybrid-domain convolutional neural network for limited-angle computed tomography imaging
    Qiyang Zhang, Zhanli Hu, Changhui Jiang · 2020 · Physics in Medicine and Biology
18. Half2Half: deep neural network based CT image denoising without independent reference data
    Nimu Yuan, Jian Zhou, Jinyi Qi · 2020 · Physics in Medicine and Biology
19. SAR Parametric Super-Resolution Image Reconstruction Methods Based on ADMM and Deep Neural Network
    Yangkai Wei, Yinchuan Li, Zegang Ding · 2021 · IEEE Transactions on Geoscience and Remote Sensing
20. CT-Scan Denoising Using a Charbonnier Loss Generative Adversarial Network
    Binit Vasant Gajera, Siddhant Raj Kapil, Dorsa Ziaei, Jayalakshmi Mangalagiri, Eliot L. Siegel, David Chapman · 2021 · IEEE Access
21. Multi‐Dimensional Characterization of Battery Materials
    R. Ziesche, T. Heenan, P. Kumari, Jarrod Williams, Wei-Qun Li, M. Curd, T. Burnett, I. Robinson, D. Brett, Matthias Joachim Ehrhardt et al. · 2023 · Advanced Energy Materials
22. All-optical image denoising using a diffractive visual processor
    Çağatay Işıl, Tianyi Gan, Fazil Onuralp Ardic, Koray Mentesoglu, Jagrit Digani, Hüseyin Karaca, Hanlong Chen, Jingxi Li, Deniz Mengü, Mona Jarrahi et al. · 2024 · Light Science & Applications
23. A Hybrid Frequency-Domain/Image-Domain Deep Network for Magnetic Resonance Image Reconstruction
    Roberto Medeiros de Souza, Richard Frayne · 2019 · SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)
24. Deep learning based image reconstruction algorithm for limited-angle translational computed tomography
    Jiaxi Wang, Jun Sheng Liang, Jingye Cheng, Yumeng Guo, Li Zeng · 2020 · PLoS ONE
25. Deep learning in magnetic resonance image reconstruction
    Shekhar S. Chandra, Marlon Bran Lorenzana, Xinwen Liu, Siyu Liu, Steffen Bollmann, ‪Stuart Crozier‬ · 2021 · Journal of Medical Imaging and Radiation Oncology
26. Rapid classification of soils from different mining areas by laser-induced breakdown spectroscopy (LIBS) coupled with a PCA-based convolutional neural network
    Wenyuan Hao, Xiaojian Hao, Yanwei Yang, Xuanda Liu, Yekun Liu, Peng Sun, Ran Sun · 2021 · Journal of Analytical Atomic Spectrometry
27. Artificial intelligence with deep learning in nuclear medicine and radiology
    Milan Decuyper, Jens Maebe, Roel Van Holen, Stefaan Vandenberghe · 2021 · EJNMMI Physics
28. Training Deep Learning Based Image Denoisers From Undersampled Measurements Without Ground Truth and Without Image Prior
    Magauiya Zhussip, Shakarim Soltanayev, Se Young Chun · 2019 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
29. Enhancement of Multimodal Microwave-Ultrasound Breast Imaging Using a Deep-Learning Technique
    Vahab Khoshdel, Ahmed Bilal Ashraf, Joe LoVetri · 2019 · Sensors
30. Learning-Assisted Multimodality Dielectric Imaging
    Guanbo Chen, Pratik Shah, John Patrick Stang, Mahta Moghaddam · 2019 · IEEE Transactions on Antennas and Propagation
31. Inverse Modeling for Filters Using a Regularized Deep Neural Network Approach
    Guangyuan Pan, Yang Wu, Ming Yu · 2020 · IEEE Microwave and Wireless Components Letters
32. Recent progress in digital image restoration techniques: A review
    Aamir Wali, Asma Naseer, Maria Tamoor · 2023 · Digital Signal Processing
33. Deep Learning Based Sinogram Correction for Metal Artifact Reduction
    Muhammad Usman Ghani, William Clem Karl · 2018 · Electronic Imaging
34. Landweber Iterative Image Reconstruction Method Incorporated Deep Learning for Electrical Resistance Tomography
    Feng Li, Feng Dong, Chao Tan · 2020 · IEEE Transactions on Instrumentation and Measurement
35. An Artificial Intelligence Multiprocessing Scheme for the Diagnosis of Osteosarcoma MRI Images
    Jia Wu, Pei Xiao, Haojie Huang · 2022 · IEEE Journal of Biomedical and Health Informatics
36. Learned Reconstruction Methods With Convergence Guarantees: A survey of concepts and applications
    Subhadip Mukherjee, Andreas Hauptmann, Ozan Öktem, Marcelo Pereyra, Carola‐Bibiane Schönlieb · 2023 · IEEE Signal Processing Magazine
37. A Partially-Learned Algorithm for Joint Photo-acoustic Reconstruction and Segmentation
    Yoeri E. Boink, Srirang Manohar, Christoph Brüne · 2019 · IEEE Transactions on Medical Imaging
38. Hybrid Deep Neural Network Scheduler for Job-Shop Problem Based on Convolution Two-Dimensional Transformation
    Zelin Zang, Wanliang Wang, Yuhang Song, Lin-Yan Lu, Weikun Li, Yule Wang, Yanwei Zhao · 2019 · Computational Intelligence and Neuroscience
39. Fidelity imposed network edit (FINE) for solving ill-posed image reconstruction
    Jinwei Zhang, Zhe Liu, Shun Zhang, Hang Zhang, Pascal Spincemaille, Thanh Duc Nguyen, Mert Rory Sabuncu, Yi Wang · 2020 · NeuroImage
40. Three-dimensional tomography of red blood cells using deep learning
    Joowon Lim, Ahmed Bassam Ayoub, Demetri Psaltis · 2020 · Advanced Photonics
41. Deep learning based spectral CT imaging
    Weiwen Wu, Dianlin Hu, Chuang Niu, Lieza Vanden Broeke, Anthony P. H. Butler, Peng Cao, James Atlas, Alexander I. Chernoglazov, Varut Vardhanabhuti, Ge Wang · 2021 · Neural Networks
42. ViTO: Vision Transformer-Operator
    Oded Ovadia, Adar Kahana, Panos Stinis · 2024 · Computer Methods in Applied Mechanics and Engineering
43. Induced-Current Learning Method for Nonlinear Reconstructions in Electrical Impedance Tomography
    Zhun Wei, Xudong Chen · 2019 · IEEE Transactions on Medical Imaging
44. Deep learning STEM-EDX tomography of nanocrystals
    Yoseob Han, Jaeduck Jang, Eunju Cha et al. · 2021 · Nature Machine Intelligence
45. DM-Fusion: Deep Model-Driven Network for Heterogeneous Image Fusion
    Xu, Guoxia, He, Chunming, Wang, Hao, Zhu, Hu, Ding, Weiping · 2024 · IEEE Transactions on Neural Networks and Learning Systems
46. Structural engineering from an inverse problems perspective
    Adrien Gallet, Sam E. Rigby, Tyler N. Tallman, Xiangxiong Kong, Iman Hajirasouliha, A. Liew, Dong Liu, Liang Chen, Andreas Hauptmann, Danny Smyl · 2022 · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
47. Multi-resolution convolutional neural networks for inverse problems
    Feng Wang, Alberto Eljarrat, Johannes Müller, Trond R. Henninen, Rolf Erni, Christoph T. Koch · 2020 · Scientific Reports
48. Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging
    Fangshu Yang, Thanh-an Pham, Nathalie Brandenberg, Matthias P. Lütolf, Jianwei Ma, Michael Unser · 2021 · IEEE Transactions on Image Processing
49. Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems
    William Herzberg, Daniel B. Rowe, Andreas Hauptmann · 2021 · IEEE Transactions on Computational Imaging
50. Deep Learning for 3-D Inversion of Gravity Data
    Lianzhi Zhang, Guibin Zhang, Yao Liu · 2021 · IEEE Transactions on Geoscience and Remote Sensing
51. Studying osteoarthritis with artificial intelligence applied to magnetic resonance imaging
    Francesco Calivá, Nikan K. Namiri, Maureen Dubreuil, Valentina Pedoia, Eugene Ozhinsky, Sharmila Majumdar · 2021 · Nature Reviews Rheumatology
52. Robust Equivariant Imaging: a fully unsupervised framework for learning to image from noisy and partial measurements
    Dongdong Chen, Julián Andrés Tachella, Mike E. Davies · 2022 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
53. A foundation model for enhancing magnetic resonance images and downstream segmentation, registration and diagnostic tasks
    Yue Sun, Limei Wang, Gang Li, Weili Lin, Li Wang · 2024 · Nature Biomedical Engineering
54. SIMBA: Scalable Inversion in Optical Tomography Using Deep Denoising Priors
    Zihui Wu, Yu Sun, Alex C. Matlock, Jiaming Liu, Lei Tian, Ulugbek S. Kamilov · 2020 · IEEE Journal of Selected Topics in Signal Processing
55. CSR-Net: A Novel Complex-Valued Network for Fast and Precise 3-D Microwave Sparse Reconstruction
    Mou Wang, Shunjun Wei, Jun Tao Shi, Yue Wu, Qizhe Qu, Yuanyuan Zhou, Xiangfeng Zeng, Bokun Tian · 2020 · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
56. Sparse-view CT reconstruction based on multi-level wavelet convolution neural network
    Minjae Lee, Hyemi Kim, Hee-Joung Kim · 2020 · Physica Medica
57. Plant miRNA–lncRNA Interaction Prediction with the Ensemble of CNN and IndRNN
    Peng Zhang, Jun Meng, Yushi Luan, Chanjuan Liu · 2019 · Interdisciplinary Sciences Computational Life Sciences
58. Solver-informed neural networks for spectrum reconstruction of colloidal quantum dot spectrometers
    Jinhui Zhang, Xueyu Zhu, Jie Bao · 2020 · Optics Express
59. Robust Reconstruction With Deep Learning to Handle Model Mismatch in Lensless Imaging
    Tianjiao Zeng, Edmund Y. M. Lam · 2021 · IEEE Transactions on Computational Imaging
60. DDPTransformer: Dual-Domain With Parallel Transformer Network for Sparse View CT Image Reconstruction
    Runrui Li, Qing Li, Hexi Wang, Saize Li, Juanjuan Zhao, Yan Qiang, Long Wang · 2022 · IEEE Transactions on Computational Imaging
61. SOM-Net: Unrolling the Subspace-Based Optimization for Solving Full-Wave Inverse Scattering Problems
    Yü Liu, Hao Zhao, Rencheng Song · 2022 · IEEE Transactions on Geoscience and Remote Sensing
62. LEARN++: Recurrent Dual-Domain Reconstruction Network for Compressed Sensing CT
    Yi Zhang, Hu Chen, Wenjun Xia, Yang Chen, Baodong Liu, Yan Liu, Huaiqiang Sun, Jiliu Zhou · 2022 · IEEE Transactions on Radiation and Plasma Medical Sciences
63. Improving 3D Imaging with Pre-Trained Perpendicular 2D Diffusion Models
    Suhyeon Lee, Hyungjin Chung, Min‐Young Park, Jonghyuk Park, Wi‐Sun Ryu, Jong Chul Ye · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
64. Stage-by-Stage Wavelet Optimization Refinement Diffusion Model for Sparse-View CT Reconstruction
    Kai Xu, Shiyu Lu, Bin Huang, Wei‐Wen Wu, Qiegen Liu · 2024 · IEEE Transactions on Medical Imaging
65. Deep iterative reconstruction for phase retrieval
    Çağatay Işıl, Figen S. Öktem, Aykut Koç · 2019 · Applied Optics
66. Tomographic reconstruction with a generative adversarial network
    Xiaogang Yang, Maik Kahnt, Dennis Brückner · 2020 · Journal of Synchrotron Radiation
67. A New Deep Learning Network for Mitigating Limited-view and Under-sampling Artifacts in Ring-shaped Photoacoustic Tomography
    Huijuan Zhang, Hongyu Li, Nikhila Nyayapathi, Depeng Wang, Alisa Le, Leslie L. Ying, Jun Xia · 2020 · Computerized Medical Imaging and Graphics
68. Learned SPARCOM: unfolded deep super-resolution microscopy
    Gili Dardikman-Yoffe, Yonina C. Eldar · 2020 · Optics Express
69. High imaging quality of Fourier single pixel imaging based on generative adversarial networks at low sampling rate
    Xu Yang, Pengfei Jiang, Mingfeng Jiang · 2021 · Optics and Lasers in Engineering
70. Compressive Imaging: Structure, Sampling, Learning
    Ben Adcock, Anders C. Hansen · 2021 · Cambridge University Press eBooks
71. Low Dose Abdominal CT Image Reconstruction: An Unsupervised Learning Based Approach
    Shiba P. Kuanar, Vassilis Athitsos, Dwarikanath Mahapatra, K.R. Rao, Zahid Akhtar, Dipankar Dasgupta · 2019 · Proceedings - International Conference on Image Processing
72. Deep‐learning‐based direct inversion for material decomposition
    Hao Gong, Shengzhen Tao, Kishore Rajendran · 2020 · Medical Physics
73. CV-GMTINet: GMTI Using a Deep Complex-Valued Convolutional Neural Network for Multichannel SAR-GMTI System
    Huilin Mu, Yun Zhang, Yicheng Jiang · 2021 · IEEE Transactions on Geoscience and Remote Sensing
74. Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications
    Johannes Leuschner, Maximilian Schmidt, Poulami Somanya Ganguly, Vladyslav Andriiashen, Sophia Bethany Coban, Alexander Denker, Dominik F. Bauer, Amir Hadjifaradji, Kees Joost Batenburg, Peter Maaß et al. · 2021 · Journal of Imaging
75. Learning Activation Functions in Deep (Spline) Neural Networks
    Pakshal Bohra, Joaquim Campos, Harshit Gupta · 2020 · IEEE Open Journal of Signal Processing
76. Learning MRI artefact removal with unpaired data
    Siyuan Liu, Kim-Han Thung, Liangqiong Qu · 2021 · Nature Machine Intelligence
77. Deep learning autofluorescence-harmonic microscopy
    Binglin Shen, Shaowen Liu, Yanping Li, Ying Pan, Yuan Lu, Rui Hu, Junle Qu, Liwei Liu · 2022 · Light Science & Applications
78. Self-Supervised Coordinate Projection Network for Sparse-View Computed Tomography
    Qing Wu, Ruimin Feng, Hongjiang Wei, Jingyi Yu A, Yuyao Zhang · 2023 · IEEE Transactions on Computational Imaging
79. Generative Modeling in Sinogram Domain for Sparse-View CT Reconstruction
    Bing Guan, Cailian Yang, Liu Zhang, Shanzhou Niu, Minghui Zhang, Yuhao Wang, Weiwen Wu, Qiegen Liu · 2023 · IEEE Transactions on Radiation and Plasma Medical Sciences
80. Landmine Detection Using Autoencoders on Multipolarization GPR Volumetric Data
    Paolo Bestagini, Federico Lombardi, Maurizio Lualdi · 2021 · Virtual Community of Pathological Anatomy (University of Castilla La Mancha)
81. Deep denoising for multi-dimensional synchrotron X-ray tomography without high-quality reference data
    Allard A. Hendriksen, Minna Bührer, Laura Leone, Marco Merlini, Nicola Viganò, Daniel Maria Pelt, Federica Marone, Marco Di Michiel, Kees Joost Batenburg · 2021 · Scientific Reports
82. Deep holography
    Guohai Situ · 2022 · Light Advanced Manufacturing
83. Deep learning inversion of Rayleigh-wave dispersion curves with geological constraints for near-surface investigations
    Xinhua Chen, Jianghai Xia, Jingyin Pang, Changjiang Zhou, Binbin Mi · 2022 · Geophysical Journal International
84. Image reconstruction algorithms in radio interferometry: From handcrafted to learned regularization denoisers
    Matthieu Terris, Arwa Dabbech, Chao Tang, Yves Wiaux · 2022 · Monthly Notices of the Royal Astronomical Society
85. A Novel Center-Boundary Metric Loss to Learn Discriminative Features for Hyperspectral Image Classification
    Shaohui Mei, Zonghao Han, Mingyang Ma, Fulin Xu, Xingang Li · 2024 · IEEE Transactions on Geoscience and Remote Sensing
86. ADMM-based deep reconstruction for limited-angle CT
    Jiaxi Wang, Li Zeng, Chengxiang Wang, Yumeng Guo · 2019 · Physics in Medicine and Biology
87. Deep learning for a space-variant deconvolution in galaxy surveys
    Florent C. Sureau, Alexis Lechat, Jean‐Luc Starck · 2020 · Astronomy and Astrophysics
88. Low-dose CT with deep learning regularization via proximal forward–backward splitting
    Qiaoqiao Ding, Gaoyu Chen, Xiaoqun Zhang, Qiu Huang, Hui Ji, Hao Gao · 2020 · Physics in Medicine and Biology
89. Learning From Synthetic Images via Active Pseudo-Labeling
    Liangchen Song, Yonghao Xu, Lefei Zhang, Bo Du, Qian Zhang, Xinggang Wang · 2020 · IEEE Transactions on Image Processing
90. Self-Supervised Dynamic CT Perfusion Image Denoising With Deep Neural Networks
    Dufan Wu, Hui Ren, Quanzheng Li · 2020 · IEEE Transactions on Radiation and Plasma Medical Sciences
91. BR$^2$Net: Defocus Blur Detection Via a Bidirectional Channel Attention Residual Refining Network
    Chang Tang, Xinwang Liu, Shan An, Pichao Wang · 2020 · IEEE Transactions on Multimedia
92. DAN-Net: Dual-domain adaptive-scaling non-local network for CT metal artifact reduction
    Tao Wang, Wenjun Xia, Yongqiang Huang · 2021 · Physics in Medicine and Biology
93. Hyperspectral Mixed Noise Removal via Spatial-Spectral Constrained Unsupervised Deep Image Prior
    Yisi Luo, Xi-Le Zhao, Tai-Xiang Jiang · 2021 · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
94. DuDoTrans: Dual-Domain Transformer for Sparse-View CT Reconstruction
    Ce Wang, Kun Shang, Haimiao Zhang, Qian Li, S. Kevin Zhou · 2022 · Lecture notes in computer science
95. Deep Learning-Based Sinogram Completion for Low-Dose CT
    Muhammad Usman Ghani, William Clem Karl · 2018 · IEEE Image, Video, and Multidimensional Signal Processing Workshop (IVMSP)
96. Deep Convolutional Neural Network for Ultrasound Image Enhancement
    Dimitris Perdios, Manuel Vonlanthen, Adrien Besson, Florian Martinez, Marcel Arditi, Jean‐Philippe Thiran · 2018 · IEEE International Ultrasonics Symposium
97. Deep Learning in MR Image Processing
    Doohee Lee, Jingu Lee, Jingyu Ko, Jaeyeon Yoon, Kanghyun Ryu, Yoonho Nam · 2019 · Investigative Magnetic Resonance Imaging
98. Compressive Sensing Spectroscopy Using a Residual Convolutional Neural Network
    Cheolsun Kim, Dongju Park, Heung-No Lee · 2020 · Sensors
99. Generative models for active vision
    Parr, Thomas, Sajid, Noor, Da Costa, Lancelot, Mirza, M. Berk, Friston, Karl J. · 2021 · Frontiers in Neurorobotics
100. Fourier ptychographic microscopy with untrained deep neural network priors
     Quan Chen, Duolan Huang, Rui Chen · 2022 · Optics Express