当前位置: X-MOL首页全球导师 国内导师 › 单洪明

个人简介

Dr. Hongming Shan is a Young Principal Investigator at the Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, and also a “Qiusuo” Research Leader at the Shanghai Center for Brain Science and Brain-inspired Technology. Before joining Fudan University in Sep. 2020, he worked with Prof. Ge Wang at the Biomedical Imaging Center, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, where he was a Postdoctoral Research Associate from Apr. 2017 to May 2020, and a Research Scientist from Jun. 2020 to Aug. 2020. He received his Ph.D. in machine learning from Fudan University in Jan. 2017, under the supervision of Prof. Junping Zhang. He has published research papers in top journals including Nature Machine Intelligence, IEEE Transactions on Cybernetics, IEEE Transactions on Medical Imaging, IEEE Transactions on Information Forensics and Security, and Medical Image Analysis. His research has been covered by several media such as NIH, RPI News, EurekAlert!, Physics world, and HealthImaging.

研究领域

机器学习、医学图像、影像组学分析、计算机视觉

近期论文

查看导师新发文章 (温馨提示:请注意重名现象,建议点开原文通过作者单位确认)

CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and Generalization Q. Gao, Z. Li, J. Zhang, Y. Zhang and H. Shan IEEE Transactions on Medical Imaging, 43(2), 745-759, 2024 Quad-Net: Quad-domain Network for CT Metal Artifact Reduction Z. Li, Q. Gao, Y. Wu, C. Niu, J. Zhang, M. Wang, G. Wang and H. Shan IEEE Transactions on Medical Imaging, 2024 (In Press) LIT-Former: Linking In-plane and Through-plane Transformers for Simultaneous CT Image Denoising and Deblurring Z. Chen, C. Niu, Q. Gao, G. Wang* and H. Shan* IEEE Transactions on Medical Imaging, 2024 (In Press) Joint Learning Framework of Cross-modal Synthesis and Diagnosis for Alzheimer's Disease by Mining Underlying Shared Modality Information C. Wang, S. Piao, Z. Huang, Q. Gao, J. Zhang, Y. Li* and H. Shan* Medical Image Analysis, 91(2024), 103032, 2024 DreamVideo: Composing Your Dream Videos with Customized Subject and Motion Y. Wei, S. Zhang, Z. Qing, H. Yuan, Z. Liu, Y. Liu, Y. Zhang, J. Zhou and H. Shan In Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle WA, USA, Jun. 17-21, 2024 Point, Segment and Count: A Generalized Framework for Object Counting Z. Huang, M. Dai, Y. Zhang, J. Zhang and H. Shan In Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle WA, USA, Jun. 17-21, 2024 HOPE: Hybrid-granularity Ordinal Prototype Learning for Progression Prediction of Mild Cognitive Impairment C. Wang, Y. Lei, T. Chen, J. Zhang, Y. Li* and H. Shan* IEEE Journal of Biomedical and Health Informatics, 2024 (In Press) CT Image Denoising and Deblurring with Deep Learning: Current Status and Perspectives Y. Lei, C. Niu*, J. Zhang, G. Wang and H. Shan* IEEE Transactions on Radiation and Plasma Medical Sciences, 8(2), 153-172, 2024 Prompt Learning in Computer Vision: A Survey Y. Lei*, J. Li, Z. Li, Y. Cao and H. Shan* Frontiers of Information Technology & Electronic Engineering, 25(1), 42-63, 2024 Promoting Fast MR Imaging Pipeline by Full-Stack AI Z. Wang, B. Li, H. Yu, Z. Zhang, M. Ran, W. Xia, Z. Yang, J. Lu, H. Chen, J. Zhou, H. Shan* and Y. Zhang* iScience, 27(1), 108608, 2024 End-to-end Paired Ambisonic-Binaural Audio Rendering Y. Zhu, Q. Kong, J. Shi, S. Liu, X. Ye, J.C. Wang, H. Shan and J. Zhang IEEE/CAA Journal of Automatica Sinica, 11(2), 502-513, 2024 Deep Rank-Consistent Pyramid Model for Enhanced Crowd Counting J. Gao, Z. Huang, Y. Lei, H. Shan, J. Z. Wang, F. Y. Wang and J. Zhang IEEE Transactions on Neural Networks and Learning Systems, 2023 (In Press) Weakly Supervised Learning-based 3D Bladder Reconstruction from 2D Ultrasound Images for Bladder Volume Measurement Z. Peng, H. Shan, X. Yang, S. Li, D. Tang, Y. Cao, Q. Shao, W. Huo and Z. Yang Medical Physics, 51(2), 1277-1288, 2024 SIAM: A Simple Alternating Mixer for Video Prediction X. Zheng, Z. Peng, Y. Cao, H. Shan and J. Zhang In Proceedings of IEEE International Conference on Multimedia and Expo (ICME), Niagara Falls, ON, Canada, Jul. 15-19, 2024 Semantic Latent Decomposition with Normalizing Flows for Face Editing B. Li, Z. Huang, H. Shan and J. Zhang In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, Apr. 14-19, 2024 The Potential and Prospects of Segment Anything Model: A Survey M. Wang, Z. Huang, H. He, H. Lu, H. Shan and J. Zhang Journal of Image and Graphics (中国图象图形学报), 2024 Learning Representation for Clustering via Prototype Scattering and Positive Sampling Z. Huang, J. Chen, J. Zhang and H. Shan IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(6), 7509-7524, 2023 When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework and A New Benchmark Z. Huang, J. Zhang and H. Shan IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(6), 7917-7932, 2023 LICO: Explainable Models with Language-Image Consistency Y. Lei, Z. Li, Y. Li, J. Zhang and H. Shan In Proceedings of International Conference on Neural Information Processing Systems (NeurIPS), New Orleans, Louisiana, USA, Dec. 10-16, 2023 Learning to Distill Global Representation for Sparse-View CT Z. Li, C. Ma, J. Chen, J. Zhang and H. Shan In Proceedings of International Conference on Computer Vision (ICCV), Paris, France, Oct. 2-6, 2023 Adaptive Nonlinear Latent Transformation for Conditional Face Editing Z. Huang, S. Ma, J. Zhang and H. Shan In Proceedings of International Conference on Computer Vision (ICCV), Paris, France, Oct. 2-6, 2023 Online Prototype Learning for Online Continual Learning Y. Wei, J. Ye, Z. Huang, J. Zhang and H. Shan In Proceedings of International Conference on Computer Vision (ICCV), Paris, France, Oct. 2-6, 2023 Twin Contrastive Learning with Noisy Labels Z. Huang, J. Zhang and H. Shan In Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, Jun. 18-22, 2023 Emo-DNA: Emotion Decoupling and Alignment Learning for Cross-Corpus Speech Emotion Recognition J. Ye, Y. Wei, X. C. Wen, C. Ma, Z. Huang, K. H. Liu and H. Shan In Proceedings of ACM International Conference on Multimedia (ACM MM), Ottawa, Ontario, Canada, Oct. 29-Nov. 2, 2023 Impact of Loss Functions on the Performance of a Deep Neural Network Designed to Restore Low-dose Digital Mammography H. Shan , R. B. Vimieiro , L. R. Borges, M. A. C. Vieira and G. Wang Artificial Intelligence In Medicine, 142(2023), 102555, 2023 M3NAS: Multi-Scale and Multi-Level Memory-Efficient Neural Architecture Search for Low-Dose CT Denoising Z. Lu, W. Xia, Y. Huang, M. Hou, H. Chen, J. Zhou, H. Shan* and Y. Zhang* IEEE Transactions on Medical Imaging, 42(3), 850-863, 2023 FreeSeed: Frequency-band-aware and Self-guided Network for Sparse-view CT Reconstruction C. Ma, Z. Li, J. Zhang, Y. Zhang and H. Shan In Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver, Canada, Oct. 8-12, 2023 ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT Denoising Z. Chen, Q. Gao, Y. Zhang and H. Shan In Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver, Canada, Oct. 8-12, 2023 CLIP-Lung: Textual Knowledge-Guided Lung Nodule Malignancy Prediction Y. Lei, Z. Li, Y. Shen, J. Zhang and H. Shan In Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver, Canada, Oct. 8-12, 2023 BerDiff: Conditional Bernoulli Diffusion Model for Medical Image Segmentation T. Chen, C. Wang and H. Shan In Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver, Canada, Oct. 8-12, 2023 Geometry Flow-based Deep Riemannian Metric Learning Y. Li, C. Fei, C. Wang, H. Shan and R. Lu IEEE/CAA Journal of Automatica Sinica, 10(9), 1882-1892, 2023 Mutual Information Boosted Reweighting for Precipitation Nowcasting from Radar Images Y. Cao, D. Zhang, X. Zheng, H. Shan and J. Zhang Remote Sensing, 15(6), 1639, 2023 Motion Matters: A Novel Motion Modeling For Cross-View Gait Feature Learning J. Li, J. Gao, Y. Zhang, H. Shan and J. Zhang In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, Jun. 4-10, 2023 GaitCoTr: Improved Spatial-Temporal Representation for Gait Recognition with a Hybrid Convolution-Transformer Framework J. Li, Y. Zhang, H. Shan and J. Zhang In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, Jun. 4-10, 2023 Mutual Information based Reweighting for Precipitation Nowcasting Y. Cao, D. Zhang, X. Zheng, H. Shan and J. Zhang In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, Jun. 4-10, 2023 Cross-Head Supervision for Crowd Counting with Noisy Annotations M. Dai, Z. Huang, J. Gao, H. Shan and J. Zhang In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, Jun. 4-10, 2023 FAN-Net: Fourier-based Adaptive Normalization for Cross-Domain Stroke Lesion Segmentation W. Yu, Y. Lei and H. Shan In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, Jun. 4-10, 2023 Temporal Modeling Matters: A Novel Temporal Emotional Modeling Approach for Speech Emotion Recognition J. Ye, X. C. Wen, Y. Wei, Y. Xu, K. H. Liu* and H. Shan* In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, Jun. 4-10, 2023 DO-FAM: Disentangled Non-Linear Latent Navigation for Facial Attribute Manipulation Y. Yuan, S. Ma, H. Shan and J. Zhang In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, Jun. 4-10, 2023 GREAT-IQA: Integrating Global Perception and Local Task-Specific Information for CT Image Quality Assessment Q. Gao, H. Shan and D. Zeng In Proceedings of IEEE International Conference on Medical Artificial Intelligence (MedAI), Beijing, China, Nov. 18-19, 2023 DSiV: Data Science for Intelligent Vehicles J. Zhang, J. Pu, J. Chen, H. Fu, Y. Tao, S. Wang, Q. Chen, Y. Xiao, S. Chen, Y. Cheng, H. Shan, D. Chen and F. Y. Wang IEEE Transactions on Intelligent Vehicles, 8(4), 2628-2634, 2023 Material Decomposition of Spectral CT Images via Attention-based Global Convolutional Generative Adversarial Network X. Guo, P. He*, X. Lv, X. Ren, Y. Li, Y. Liu, X. Lei, P. Feng and H. Shan* Nuclear Science and Techniques, 34(3), 45, 2023 SAN-Net: Learning Generalization to Unseen Sites for Stroke Lesion Segmentation with Self-Adaptive Normalization W. Yu, Z. Huang, J. Zhang and H. Shan Computers in Biology and Medicine, 156, 106717, 2023 Physics-/Model-Based and Data-Driven Methods for Low-Dose Computed Tomography: A Survey W. Xia, H. Shan, G. Wang and Y. Zhang IEEE Signal Processing Magazine, 40(2), 89-100, 2023 Forget Less, Count Better: A Domain-Incremental Self-Distillation Learning Benchmark for Lifelong Crowd Counting J. Gao, J. Li, H. Shan, Y. Qu, J. Z. Wang, F. Y. Wang and J. Zhang Frontiers of Information Technology & Electronic Engineering, 24(2), 187-202, 2023 A Survey of Deep Learning-Based MRI Stroke Lesion Segmentation Methods W. Yu, T. Chen, J. Zhang and H. Shan Chinese Journal of Intelligent Science and Technology (智能科学与技术学报), 5(3), 293-312, 2023 SPICE: Semantic Pseudo-Labeling for Image Clustering C. Niu, H. Shan* and G. Wang* IEEE Transactions on Image Processing, 31, 7264-7278, 2022 Meta Ordinal Regression Forest for Medical Image Classification with Ordinal Labels Y. Lei, H. Zhu, J. Zhang and H. Shan IEEE/CAA Journal of Automatica Sinica, 9(7), 1233-1247, 2022 DU-GAN: Generative Adversarial Networks with Dual-Domain U-Net Based Discriminators for Low-Dose CT Denoising Z. Huang, J. Zhang, Y. Zhang and H. Shan IEEE Transactions on Instrumentation and Measurement, 71, 4500512, 2022 Convolutional Ordinal Regression Forest for Image Ordinal Estimation H. Zhu , H. Shan , Y. Zhang, L. Che, X. Xu, J. Zhang, J. Shi and F. Y. Wang IEEE Transactions on Neural Networks and Learning Systems, 33(7), 4084-4095, 2022 CoCoDiff: A Contextual Conditional Diffusion Model for Low-dose CT Image Denoising Q. Gao and H. Shan In Proceedings of SPIE 12242, Developments in X-Ray Tomography XIV, San Diego, California, United States, Aug. 22-24, 2022 OpenKBP-Opt: An International and Reproducible Evaluation of 76 Knowledge-Based Planning Pipelines A. Babier, et al. Physics in Medicine and Biology, 67(18), 185012, 2022 Low-Dimensional Manifold Constrained Disentanglement Network for Metal Artifact Reduction C. Niu, W. Cong, F. Fan, H. Shan, M. Li, J. Liang and G. Wang IEEE Transactions on Radiation and Plasma Medical Sciences, 6(6), 656-666, 2022 Stabilizing Deep Tomographic Reconstruction: Part A. Hybrid Framework and Experimental Results W. Wu, D. Hu, W. Cong, H. Shan, S. Wang, C. Niu, P. Yan, H. Yu, V. Vardhanabhuti and G. Wang Patterns, 3, 100474, 2022 Stabilizing Deep Tomographic Reconstruction: Part B. Convergence Analysis and Adversarial Attacks W. Wu, D. Hu, W. Cong, H. Shan, S. Wang, C. Niu, P. Yan, H. Yu, V. Vardhanabhuti and G. Wang Patterns, 3, 100475, 2022 Hybrid Weighting Loss for Precipitation Nowcasting from Radar Images Y. Cao, L. Chen, D. Zhang, L. Ma and H. Shan Proceedings of IEEE International Conference on Acoustics, Speech, & Signal Processing (ICASSP), Singapore, May 22-27, 2022 Low-Dose CT Denoising via Neural Architecture Search Z. Lu, W. Xia, Y. Huang, M. Hou, H. Chen, H. Shan* and Y. Zhang* Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI), ITC Royal Bengal, Kolkata, India, Mar. 28-31, 2022. Content-Noise Complementary Learning for Medical Image Denoising M. Geng, X. Meng, J. Yu, L. Zhu, L. Jin, Z. Jiang, B. Qiu, H. Li, H. Kong, J. Yuan, K. Yang, H. Shan, H. Han, Z. Yang, Q. Ren and Y. Lu IEEE Transactions on Medical Imaging, 41(2), 407-419, 2022 A Survey of Problem Setting-driven Deep Reinforcement Learning Z. Zhang, B. Zhao, H. Shan and J. Zhang Pattern Recognition and Artificial Intelligence (模式识别与人工智能), 35(8), 718-742, 2022 When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework Z. Huang, J. Zhang and H. Shan In Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Online, Jun. 19-25, 2021 AgeFlow: Conditional Age Progression and Regression with Normalizing Flows Z. Huang, S. Chen, J. Zhang and H. Shan In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Online, Aug. 21-26, 2021 PFA-GAN: Progressive Face Aging with Generative Adversarial Network Z. Huang, S. Chen, J. Zhang and H. Shan IEEE Transactions on Information Forensics and Security, 16, 2031-2045, 2021 Deep Learning Predicts Cardiovascular Disease Risks from Lung Cancer Screening Low Dose Computed Tomography H. Chao, H. Shan, F. Homayounieh, R. Singh, R. D. Khera, H. Guo, T. Su, G. Wang, M. K. Kalra and P. Yan Nature Communications, 12, 2963, 2021 Strided Self-Supervised Low-Dose CT Denoising for Lung Nodule Classification Y. Lei, J. Zhang and H. Shan Phenomics, 1(6), 257-268, 2021 An Ensemble Learning Method Based on Ordinal Regression for COVID-19 Diagnosis from Chest CT X. Guo, Y. Lei, P. He*, W. Zeng, R. Yang, Y. Ma, P. Feng, Q. Lyu, G. Wang and H. Shan* Physics in Medicine and Biology, 66, 244001, 2021 Application of Deep-Learning Based Monte Carlo Denoising for Fast Radiation Treatment Dose Calculations Z. Peng, H. Shan, J. Zhou, X. Pei, A. Wu and X. G. Xu Proceedings of IEEE International Conference on Medical Imaging Physics and Engineering (ICMIPE), Hefei, China, Nov. 12-14, 2021 Feasibility Evaluation of PET Scan-Time Reduction for Diagnosing Amyloid-β Levels in Alzheimer’s Disease Patients Using a Deep-Learning-based Denoising Algorithm Z. Peng, M. Ni, H. Shan, Y. Lu, Y. Li, Y. Zhang, X. Pei, Z. Chen, S. Wang and X. G. Xu Computers in Biology and Medicine, 138, 104919, 2021 Cine Cardiac MRI Motion Artifact Reduction Using a Recurrent Neural Network Q. Lyu, H. Shan, Y. Xie, A. Kwan, Y. Otaki, K. Kuronuma, D. Li and G. Wang IEEE Transactions on Medical Imaging, 40(8), 2170-2181, 2021 Meta Ordinal Weighting Net for Improving Lung Nodule Classification Y. Lei, H. Shan and J. Zhang In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Toronto, Ontario, Canada, Jun. 6-11, 2021 RoutingGAN: Routing Age Progression and Regression with Disentangled Learning Z. Huang, J. Zhang and H. Shan In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Toronto, Ontario, Canada, Jun. 6-11, 2021 SelfGait: A Spatiotemporal Representation Learning Method for Self-Supervised Gait Recognition Y. Liu, Y. Zeng, J. Pu, H. Shan, P. He and J. Zhang In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Toronto, Ontario, Canada, Jun. 6-11, 2021 Optimized Collusion Prevention for Online Exams during Social Distancing M. Li, L. Luo, S. Sikdar, N. I. Nizam, S. Gao, H. Shan, M. Kruger, U. Kruger, H. Mohamed, L. Xia and G. Wang npj Science of Learning, 6, 5, 2021 Parameter-Transferred Wasserstein Generative Adversarial Network (PT-WGAN) for Low Dose PET Image Denoising Y. Gong, H. Shan, Y. Teng, N. Tu, M. Li, G. Liang, G. Wang and S. Wang IEEE Transactions on Radiation and Plasma Medical Sciences, 5(2), 213-223, 2021 Synergizing Medical Imaging and Radiotherapy with Deep Learning H. Shan , X. Jia , P. Yan, Y. Li, H. Paganetti and G. Wang Machine Learning: Science and Technology, 1(2), 021001, 2020 Multi-Contrast Super-Resolution MRI Through a Progressive Network Q. Lyu, H. Shan*, C. Steber, C. Helis, C. Whitlow, M. Chan* and G. Wang* IEEE Transactions on Medical Imaging, 39(9), 2738-2749, 2020 Meta Ordinal Regression Forests for Learning with Indeterminate Lung Nodules Y. Lei, H. Zhu, J. Zhang and H. Shan In Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Online, Dec. 16-19, 2020 Deep Efficient End-to-end Reconstruction (DEER) Network for Few-view Breast CT Image Reconstruction H. Xie, H. Shan*, W. Cong, X. Zhang, S. Liu, R. Ning and G. Wang* IEEE Access, 8, 196633-196646, 2020 A Method of Rapid Quantification of Patient‐Specific Organ Doses for CT Using Deep‐Learning based Multi‐Organ Segmentation and GPU‐accelerated Monte Carlo Dose Computing Z. Peng, X. Fang, P. Yan, H. Shan, T. Liu, X. Pei, G. Wang, B. Liu, M. K. Kalra and X. G. Xu Medical Physics, 47(6), 2526-2536, 2020 Quadratic Autoencoder (Q-AE) for Low-Dose CT Denoising F. Fan, H. Shan, M. K. Kalra, R. Singh, G. Qian, M. Getzin, Y. Teng, J. Hahn and G. Wang IEEE Transactions on Medical Imaging, 39(6), 2035-2050, 2020 Deep Adversarial Network for Super Stimulated Emission Depletion Imaging M. Li, H. Shan, S. Pryshchep, M. M. Lopez and G. Wang Journal of Nanophotonics, 14(1), 016009, 2020 MRI Super-Resolution with Ensemble Learning and Complementary Priors Q. Lyu, H. Shan and G. Wang IEEE Transactions on Computational Imaging, 6, 615-624, 2020 Look Globally, Age Locally: Face Aging with an Attention Mechanism H. Zhu, Z. Huang, H. Shan and J. Zhang In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, May 4-8, 2020 3D Few-view CT Image Reconstruction with Deep Learning H. Xie, H. Shan and G. Wang In Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI) Workshop, Iowa City, Iowa, USA, Apr. 3-7, 2020 Deeply-Supervised Multi-Dosage Prior Learning for Low-Dose PET Imaging Y. Gong, H. Shan, Y. Teng, H. Zheng, G. Wang and S. Wang In Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI) Workshop, Iowa City, Iowa, USA, Apr. 3-7, 2020 Low-Dose PET Image Restoration with 2D and 3D Network Prior Learning Y. Gong, H. Shan, Y. Teng, H. Zheng, G. Wang and S. Wang In Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI) Workshop, Iowa City, Iowa, USA, Apr. 3-7, 2020 Ordinal Distribution Regression for Gait-based Age Estimation H. Zhu, Y. Zhang, G. Li, J. Zhang and H. Shan SCIENCE CHINA Information Sciences, 63(2), 120102, 2020 Shape and Margin-Aware Lung Nodule Classification in Low-Dose CT Images via Soft Activation Mapping Y. Lei, Y. Tian, H. Shan, J. Zhang, G. Wang and M. K. Kalra Medical Image Analysis, 60(2020), 101628, 2020 CT Super-Resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble (GAN-CIRCLE) C. You, G. Li, Y. Zhang, X. Zhang, H. Shan, S. Ju, Z. Zhao, Z. Zhang, W. Cong, M. Vannier, P. Saha, E. A. Hoffman and G. Wang IEEE Transactions on Medical Imaging, 39(1), 188-203, 2020 Competitive Performance of a Modularized Deep Neural Network Compared to Commercial Algorithms for Low-Dose CT Image Reconstruction H. Shan, A. Padole, F. Homayounieh, U. Kruger, R. D. Khera, C. Nitiwarangkul, M. K. Kalra and G. Wang Nature Machine Intelligence, 1(6), 269–276, 2019 Framework of Randomized Distribution Features for Visual Representation and Categorization H. Shan, J. Zhang and U. Kruger IEEE Transactions on Cybernetics, 49(9), 3599-3606, 2019 Accelerated Correction of Reflection Artifacts by Deep Neural Networks in Photo-Acoustic Tomography H. Shan, G. Wang and Y. Yang Applied Sciences, 9, 2615, 2019 Simultaneous Reconstruction of the Initial Pressure and Sound Speed in Photoacoustic Tomography Using a Deep-Learning Approach H. Shan, C. Wiedeman, G. Wang and Y. Yang In Proceedings of SPIE 11105, Novel Optical Systems, Methods, and Applications XXII, 1110504, San Diego, California, United States, Aug. 11-15, 2019 Low-Dose CT Simulation with a Generative Adversarial Network H. Shan, X. Jia, K. Mueller, U. Kruger and G. Wang In Proceedings of SPIE 11113, Developments in X-Ray Tomography XII, 111131F, San Diego, California, United States, Aug. 11-15, 2019 A Novel Transfer Learning Framework for Low-Dose CT H. Shan, U. Kruger and G. Wang In Proceedings of SPIE 11072, the 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), 110722Y, Philadelphia, PA, USA, June 2-6, 2019 MCDNet – A Denoising Convolutional Neural Network to Accelerate Monte Carlo Radiation Transport Simulations: A Proof of Principle with Patient Dose from X-Ray CT Imaging Z. Peng , H. Shan , T. Liu, X. Pei, G. Wang and X. G. Xu IEEE Access, 7, 76680-76689, 2019 Deep Encoder-Decoder Adversarial Reconstruction (DEAR) Network for 3D CT from Few-View Data H. Xie, H. Shan and G. Wang Bioengineering, 6(4), 111, 2019 A Dual-Stream Deep Convolutional Network for Reducing Metal Streak Artifacts in CT Images L. Gjesteby, H. Shan, Q. Yang, Y. Xi, Y. Jin, D. Giantsoudi, H. Paganetti, B. De Man and G. Wang Physics in Medicine and Biology, 64(23), 235003, 2019 Deep-Learning-based Breast CT for Radiation Dose Reduction W. Cong, H. Shan, X. Zhang, S. Liu, R. Ning and G. Wang In Proceedings of SPIE 11113, Developments in X-Ray Tomography XII, 111131L, San Diego, California, United States, Aug. 11-15, 2019 Dual Network Architecture for Few-View CT - Trained on ImageNet Data and Transferred for Medical Imaging H. Xie, H. Shan, W. Cong, X. Zhang, S. Liu, R. Ning and G. Wang In Proceedings of SPIE 11113, Developments in X-Ray Tomography XII, 111130V, San Diego, California, United States, Aug. 11-15, 2019 Quadratic Neural Networks for CT Metal Artifact Reduction F. Fan, H. Shan, L. Gjesteby and G. Wang In Proceedings of SPIE 11113, Developments in X-Ray Tomography XII, 111130W, San Diego, California, United States, Aug. 11-15, 2019 Super-Resolution MRI and CT Through GAN-CIRCLE Q. Lyu, C. You, H. Shan, Y. Zhang and G. Wang In Proceedings of SPIE 11113, Developments in X-Ray Tomography XII, 111130X, San Diego, California, United States, Aug. 11-15, 2019 Deep Learning Based CT Thermometry for Thermal Tumor Ablation N. Wang, M. Li, H. Shan and P. Yan In Proceedings of SPIE 11113, Developments in X-Ray Tomography XII, 111131T, San Diego, California, United States, Aug. 11-15, 2019 A Two-dimensional Feasibility Study of Deep Learning-based Feature Detection and Characterization Directly from CT Sinograms Q. De Man, E. Haneda, B. Claus, P. Fitzgerald, B. De Man, G. Qian, H. Shan, J. Min, M. Sabuncu and G. Wang Medical Physics, 46(12), e790-e800, 2019 Quadratic Autoencoder for Low-Dose CT Denoising F. Fan, H. Shan and G. Wang In Proceedings of SPIE 11072, the 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), 110722Z, Philadelphia, PA, USA, June 2-6, 2019 Crowd Counting with Limited Labeling through Submodular Frame Selection Q. Zhou, J. Zhang, L. Che, H. Shan and J. Wang IEEE Transactions on Intelligent Transportation Systems, 20(5), 1728-1738, 2019 Multi-Task GANs for View-Specific Feature Learning in Gait Recognition Y. He, J. Zhang, H. Shan and L. Wang IEEE Transactions on Information Forensics and Security, 14(1), 102-113, 2019 3-D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning From a 2-D Trained Network H. Shan, Y. Zhang, Q. Yang, U. Kruger, M. K. Kalra, L. Sun, W. Cong and G. Wang IEEE Transactions on Medical Imaging, 37(6), 1522-1534, 2018 Real-Valued Multivariate Dimension Reduction: A Survey H. Shan and J. Zhang Acta Automatica Sinica (自动化学报), 44(2), 192-215, 2018 Structurally-Sensitive Multi-Scale Deep Neural Network for Low-Dose CT Denoising C. You, Q. Yang, H. Shan, L. Gjesteby, L. Guang, S. Ju, Z. Zhang, Z. Zhao, Y. Zhang, W. Cong and G. Wang IEEE Access, 6, 41839-41855, 2018 Deep Neural Network for CT Metal Artifact Reduction with a Perceptual Loss Function L. Gjesteby, H. Shan, Q. Yang, Y. Xi, B. Claus, Y. Jin, B. De Man and G. Wang In Proceedings of The Fifth International Conference on Image Formation in X-ray Computed Tomography (CTMeeting), Salt Lake City, Utah, USA, May 20-23, 2018 A Maximum Contributed Component Regression for the Inverse Problem in Optical Scatterometry H. Zhu, Y. Lee, H. Shan and J. Zhang Optics Express, 25(14), 15956-15966, 2017 Population Density-based Hospital Recommendation with Mobile LBS Big Data H. Chao, Y. Cao, J. Zhang, F. Xia, Y. Zhou and H. Shan In Proceedings of IEEE International Conference on Big Data and Smart Computing (BigComp), Shanghai, China, Jan. 15-18, 2018 Enhancing Transferability of Features from Pretrained Deep Neural Networks for Lung Nodule Classification H. Shan, G. Wang, M. K. Kalra, R. C. de Souza and J. Zhang In Proceedings of the 14th International Conference on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), Xi'an, China, June 18-23, 2017 Deep Learning Methods for CT Image-Domain Metal Artifact Reduction L. Gjesteby, Q. Yang, Y. Xi, H. Shan, B. Claus, Y. Jin, B. De Man and G. Wang In Proceedings of SPIE 10391, Developments in X-Ray Tomography XI, 103910W, San Diego, California, United States, Aug. 6-10, 2017

推荐链接
down
wechat
bug