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Feng Yang 0010
Person information
- affiliation: National Institutes of Health, National Library of Medicine, Lister Hill National Center for Biomedical Communications, Bethesda, MD, USA
- affiliation (2012 - 2019): Beijing Jiaotong University, Department of Biomedical Engineering, Beijing, China
- affiliation (PhD 2011): National Institute of Applied Science (INSA), Lyon, France
Other persons with the same name
- Feng Yang — disambiguation page
- Feng Yang 0001 — Northwestern Polytechnical University, School of Automation, MOE, Key laboratory of Information Fusion Technology, Xi'an, China
- Feng Yang 0002 — Beihang University, School of Computer Science and Engineering, Beijing Key Laboratory of Digital Media, China
- Feng Yang 0003 — Wuhan University, School of Resource and Environmental Sciences, China (and 1 more)
- Feng Yang 0004 — Chongqing University, State Key Laboratory of Power Transmission Equipment and System Security and New Technology, China
- Feng Yang 0005 — University of Science and Technology of China, School of Management, Hefei, China
- Feng Yang 0006 — Shanghai Jiao Tong University, Department of Electronic Engineering, Institute of Wireless Communication Technology, Cooperative Medianet Innovation Center, China
- Feng Yang 0007 — China University of Mining and Technology, School of Mechanical Electronic and Information Engineering, Beijing, China
- Feng Yang 0008 — Google Research, Mountain View, CA, USA
- Feng Yang 0009 — Shandong Normal University, School of Information Science and Engineering, Jinan, China
- Feng Yang 0011 — Agency for Science, Technology and Research (A STAR), Institute of High Performance Computing, Department of Computing Science, Singapore (and 1 more)
- Feng Yang 0012 — Southern Medical University, School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing, Guangzhou, China
- Feng Yang 0013 — University of Science and Technology of China, Department of Automation, Hefei Comprehensive National Science Center, Institute of Artificial Intelligence, Hefei, China
- Feng Yang 0014 — Guangxi University, School of Computer, Electronics and Information, Guangxi Key Laboratory of Multimedia Communications Network Technology, Nanning, China (and 1 more)
- Feng Yang 0015 — Chongqing University of Posts and Telecommunications, School of Communication and Information Engineering, Chongqing Key Laboratory of Signal and Information Processing, Chongqing, China
- Feng Yang 0016 — West Virginia University, Industrial and Management Systems Engineering, Morgantown, WV, USA (and 1 more)
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2020 – today
- 2024
- [j21]Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang, Zhaohui Liang, Zhiyun Xue, Sameer K. Antani:
Semantically redundant training data removal and deep model classification performance: A study with chest X-rays. Comput. Medical Imaging Graph. 115: 102379 (2024) - 2023
- [j20]Feng Yang, Ghada Zamzmi, Sandeep Angara, Sivaramakrishnan Rajaraman, André Aquilina, Zhiyun Xue, Stefan Jäger, Emmanouil Papagiannakis, Sameer K. Antani:
Assessing Inter-Annotator Agreement for Medical Image Segmentation. IEEE Access 11: 21300-21312 (2023) - [j19]Vy C. B. Bui, Ziv Yaniv, Michael Harris, Feng Yang, Karthik Kantipudi, Darrell E. Hurt, Alex Rosenthal, Stefan Jäger:
Combining Radiological and Genomic TB Portals Data for Drug Resistance Analysis. IEEE Access 11: 84228-84240 (2023) - [j18]Sivaramakrishnan Rajaraman, Feng Yang, Ghada Zamzmi, Zhiyun Xue, Sameer K. Antani:
Can deep adult lung segmentation models generalize to the pediatric population? Expert Syst. Appl. 229(Part A): 120531 (2023) - [c20]Tochi Oguguo, Ghada Zamzmi, Sivaramakrishnan Rajaraman, Feng Yang, Zhiyun Xue, Sameer K. Antani:
A Comparative Study of Fairness in Medical Machine Learning. ISBI 2023: 1-5 - [c19]Zhaohui Liang, Zhiyun Xue, Sivaramakrishnan Rajaraman, Feng Yang, Sameer K. Antani:
Automatic Quantification of COVID-19 Pulmonary Edema by Self-supervised Contrastive Learning. MILLanD@MICCAI 2023: 128-137 - [e1]Zhiyun Xue, Sameer K. Antani, Ghada Zamzmi, Feng Yang, Sivaramakrishnan Rajaraman, Sharon Xiaolei Huang, Marius George Linguraru, Zhaohui Liang:
Medical Image Learning with Limited and Noisy Data - Second International Workshop, MILLanD 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings. Lecture Notes in Computer Science 14307, Springer 2023, ISBN 978-3-031-47196-4 [contents] - [i6]Sivaramakrishnan Rajaraman, Feng Yang, Ghada Zamzmi, Zhiyun Xue, Sameer K. Antani:
Does image resolution impact chest X-ray based fine-grained Tuberculosis-consistent lesion segmentation? CoRR abs/2301.04032 (2023) - [i5]Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang, Zhaohui Liang, Zhiyun Xue, Sameer K. Antani:
Semantically Redundant Training Data Removal and Deep Model Classification Performance: A Study with Chest X-rays. CoRR abs/2309.09773 (2023) - [i4]Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang, Zhaohui Liang, Zhiyun Xue, Sameer K. Antani:
Uncovering the effects of model initialization on deep model generalization: A study with adult and pediatric Chest X-ray images. CoRR abs/2309.11318 (2023) - 2022
- [j17]Feng Yang, Pu Xuan Lu, Min Deng, Yi-Xiang J. Wang, Sivaramakrishnan Rajaraman, Zhiyun Xue, Les R. Folio, Sameer K. Antani, Stefan Jäger:
Annotations of Lung Abnormalities in the Shenzhen Chest X-ray Dataset for Computer-Aided Screening of Pulmonary Diseases. Data 7(7): 95 (2022) - [j16]Li-Hui Wang, Yao Hong, Yongbin Qin, Xinyu Cheng, Feng Yang, Jie Yang, Yue-Min Zhu:
Connecting macroscopic diffusion metrics of cardiac diffusion tensor imaging and microscopic myocardial structures based on simulation. Medical Image Anal. 77: 102325 (2022) - [c18]Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang, Zhiyun Xue, Sameer K. Antani:
Data Characterization for Reliable AI in Medicine. RTIP2R 2022: 3-11 - [i3]Sivaramakrishnan Rajaraman, Feng Yang, Ghada Zamzmi, Peng Guo, Zhiyun Xue, Sameer K. Antani:
Deep ensemble learning for segmenting tuberculosis-consistent manifestations in chest radiographs. CoRR abs/2206.06065 (2022) - [i2]Sivaramakrishnan Rajaraman, Feng Yang, Ghada Zamzmi, Zhiyun Xue, Sameer K. Antani:
Generalizability of Deep Adult Lung Segmentation Models to the Pediatric Population: A Retrospective Study. CoRR abs/2211.02475 (2022) - 2021
- [j15]Pei Niu, Lihuiwang, Bingqing Xie, Marc C. Robini, Loïc Boussel, Phillippe Douek, Yuemin Zhu, Feng Yang:
Improved Image Reconstruction Using Multi-Energy Information in Spectral Photon-Counting CT. IEEE Access 9: 97981-97989 (2021) - [j14]Bingqing Xie, Yuemin Zhu, Pei Niu, Ting Su, Feng Yang, Lihui Wang, Pierre-Antoine Rodesch, Loïc Boussel, Philippe Douek, Philippe Duvauchelle:
Super-Energy-Resolution Material Decomposition for Spectral Photon-Counting CT Using Pixel-Wise Learning. IEEE Access 9: 168485-168495 (2021) - [j13]Yasmin M. Kassim, Kannappan Palaniappan, Feng Yang, Mahdieh Poostchi, Nila Palaniappan, Richard James Maude, Sameer K. Antani, Stefan Jäger:
Clustering-Based Dual Deep Learning Architecture for Detecting Red Blood Cells in Malaria Diagnostic Smears. IEEE J. Biomed. Health Informatics 25(5): 1735-1746 (2021) - [c17]Deniz Kavzak Ufuktepe, Feng Yang, Yasmin M. Kassim, Hang Yu, Richard James Maude, Kannappan Palaniappan, Stefan Jaeger:
Deep Learning-Based Cell Detection and Extraction in Thin Blood Smears for Malaria Diagnosis. AIPR 2021: 1-6 - [c16]Feng Yang, Hang Yu, Karthik Kantipudi, Alex Rosenthal, Darrell E. Hurt, Ziv Yaniv, Stefan Jaeger:
Automated Drug-Resistant TB Screening: Importance of Demographic Features and Radiological Findings in Chest X-Ray. AIPR 2021: 1-4 - [c15]Manohar Karki, Karthik Kantipudi, Hang Yu, Feng Yang, Yasmin M. Kassim, Ziv Yaniv, Stefan Jäger:
Identifying Drug-Resistant Tuberculosis in Chest Radiographs: Evaluation of CNN Architectures and Training Strategies. EMBC 2021: 2964-2967 - [c14]Yunlong He, Lihui Wang, Feng Yang, Yong Xia, Patrick Clarysse, Yuemin Zhu:
Systematic Study of Joint Influence of Angular Resolution and Noise in Cardiac Diffusion Tensor Imaging. FIMH 2021: 200-210 - [d1]Feng Yang, Mahdieh Poostchi, Hang Yu, Zhou Zhou, Kamolrat Silamut, Jian Yu, Richard James Maude, Stefan Jaeger, Sameer K. Antani:
Malaria Thick Blood Smears. IEEE DataPort, 2021 - 2020
- [j12]Marc C. Robini, Feng Yang, Yuemin Zhu:
A stochastic approach to full inverse treatment planning for charged-particle therapy. J. Glob. Optim. 77(4): 853-893 (2020) - [j11]Feng Yang, Mahdieh Poostchi, Hang Yu, Zhou Zhou, Kamolrat Silamut, Jian Yu, Richard James Maude, Stefan Jäger, Sameer K. Antani:
Deep Learning for Smartphone-Based Malaria Parasite Detection in Thick Blood Smears. IEEE J. Biomed. Health Informatics 24(5): 1427-1438 (2020) - [c13]Feng Yang, Nicolas Quizon, Hang Yu, Kamolrat Silamut, Richard James Maude, Stefan Jaeger, Sameer K. Antani:
Cascading YOLO: automated malaria parasite detection for Plasmodium vivax in thin blood smears. Medical Imaging: Computer-Aided Diagnosis 2020
2010 – 2019
- 2019
- [j10]Zhouxia Li, Zhiwen Pan, Xiaoni Wang, Wen Ji, Feng Yang:
Intelligence level analysis for crowd networks based on business entropy. Int. J. Crowd Sci. 3(3): 249-266 (2019) - [j9]Xiaoni Wang, Zhiwen Pan, Zhouxia Li, Wen Ji, Feng Yang:
Adaptive information sharing approach for crowd networks based on two stage optimization. Int. J. Crowd Sci. 3(3): 284-302 (2019) - [j8]Chun-Yu Chu, Chang-Yu Sun, Zi-Xiang Kuai, Feng Yang, Yue-Min Zhu:
Structure Prior Constrained Estimation of Human Cardiac Diffusion Tensors. IEEE Trans. Biomed. Eng. 66(11): 3220-3230 (2019) - [c12]Feng Yang, Hang Yu, Kamolrat Silamut, Richard James Maude, Stefan Jäger, Sameer K. Antani:
Parasite Detection in Thick Blood Smears Based on Customized Faster-RCNN on Smartphones. AIPR 2019: 1-4 - [c11]Xiaoni Wang, Zhiwen Pan, Zhouxia Li, Yifan Du, Yuanlin Zhu, Wen Ji, Feng Yang:
Optimizing Information Sharing in Crowd Networks based on Reinforcement Learning. ICCSE 2019: 6-11 - [c10]Tiantian Miao, Yuhong Shen, Lihui Wang, Wen Ji, Yuemin Zhu, Feng Yang:
Intelligent Network Application in Computer-aided Diagnosis. ICCSE 2019: 228-232 - [c9]Feng Yang, Hang Yu, Kamolrat Silamut, Richard James Maude, Stefan Jaeger, Sameer K. Antani:
Smartphone-Supported Malaria Diagnosis Based on Deep Learning. MLMI@MICCAI 2019: 73-80 - [i1]Zeyu Deng, Lihui Wang, Zi-Xiang Kuai, Qijian Chen, Xinyu Cheng, Feng Yang, Jie Yang, Yuemin Zhu:
CNN-Based Invertible Wavelet Scattering for the Investigation of Diffusion Properties of the In Vivo Human Heart in Diffusion Tensor Imaging. CoRR abs/1912.07776 (2019) - 2018
- [j7]Stefan Jäger, Octavio H. Juarez-Espinosa, Sema Candemir, Mahdieh Poostchi, Feng Yang, Lewis Kim, Meng Ding, Les R. Folio, Sameer K. Antani, Andrei E. Gabrielian, Darrell E. Hurt, Alex Rosenthal, George R. Thoma:
Detecting drug-resistant tuberculosis in chest radiographs. Int. J. Comput. Assist. Radiol. Surg. 13(12): 1915-1925 (2018) - [j6]Marc C. Robini, Feng Yang, Yuemin Zhu:
Inexact Half-Quadratic Optimization for Linear Inverse Problems. SIAM J. Imaging Sci. 11(2): 1078-1133 (2018) - [c8]Yifan Du, Yuanlin Zhu, Shengjie Wu, Lihui Wang, Yuemin Zhu, Feng Yang:
Automatic Segmentation of Left Myocardium in CMR Based on Fully Convolutional Networks. ICCSE 2018: 21:1-21:4 - 2017
- [j5]Marc C. Robini, Matthew Ozon, Carole Frindel, Feng Yang, Yue Min Zhu:
Global Diffusion Tractography by Simulated Annealing. IEEE Trans. Biomed. Eng. 64(3): 649-660 (2017) - [c7]Shengjie Wu, Feng Yang, Haoyuan Ma, Gaoyun An:
An automatic segmentation method of left myocardium based on SSD model and CNN. ISPACS 2017: 12-16 - [c6]Haoyuan Ma, Gaoyun An, Shengjie Wu, Feng Yang:
A Region Histogram of Oriented Optical Flow (RHOOF) feature for apex frame spotting in micro-expression. ISPACS 2017: 281-286 - 2016
- [c5]Hong-bo Du, Lihui Wang, Wanyu Liu, Feng Yang, Zhi Li, Yue-Min Zhu:
Diffusion MRI simulation for human brain based on the atlas. ISBI 2016: 898-902 - 2015
- [j4]Hongying Li, Marc C. Robini, Feng Yang, Isabelle E. Magnin, Yue Min Zhu:
Cardiac Fiber Unfolding by Semidefinite Programming. IEEE Trans. Biomed. Eng. 62(2): 582-592 (2015) - [j3]Hongjiang Wei, Magalie Viallon, Bénédicte M. A. Delattre, Kevin Moulin, Feng Yang, Pierre Croisille, Yue Min Zhu:
Free-Breathing Diffusion Tensor Imaging and Tractography of the Human Heart in Healthy Volunteers Using Wavelet-Based Image Fusion. IEEE Trans. Medical Imaging 34(1): 306-316 (2015) - 2014
- [j2]Feng Yang, Yue-Min Zhu, Jianhua Luo, Marc C. Robini, Jie Liu, Pierre Croisille:
A Comparative Study of Different Level Interpolations for Improving Spatial Resolution in Diffusion Tensor Imaging. IEEE J. Biomed. Health Informatics 18(4): 1317-1327 (2014) - [c4]Lihui Wang, Yue-Min Zhu, Feng Yang, Wanyu Liu, Isabelle E. Magnin:
Simulation of dynamic DTI of 3D cardiac fiber structures. ISBI 2014: 714-717 - 2012
- [j1]Feng Yang, Yue-Min Zhu, Isabelle E. Magnin, Jianhua Luo, Pierre Croisille, Peter B. Kingsley:
Feature-based interpolation of diffusion tensor fields and application to human cardiac DT-MRI. Medical Image Anal. 16(2): 459-481 (2012) - [c3]Tao Wu, Ling Xia, Feng Yang:
Registration of cardiac diffusion tensor images using B-spline free-form deformation. BMEI 2012: 344-347 - [c2]Hongying Li, Marc C. Robini, Feng Yang, Yuemin Zhu:
A neighborhood-based probabilistic approach for fiber tracking in human cardiac DTI. ISBI 2012: 9-13
2000 – 2009
- 2009
- [c1]Feng Yang, Xin Song, Stanislas Rapacchi, Laurent Fanton, Pierre Croisille, Yue-Min Zhu:
Noise-Reduced TPS Interpolation of Primary Vector Fields for Fiber Tracking in Human Cardiac DT-MRI. FIMH 2009: 78-86
Coauthor Index
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