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Bruno De Man
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2020 – today
- 2024
- [j17]Grigorios M. Karageorgos
, Jiayong Zhang, Nils Peters, Wenjun Xia
A Denoising Diffusion Probabilistic Model for Metal Artifact Reduction in CT. IEEE Trans. Medical Imaging 43(10): 3521-3532 (2024) - [j16]Christopher Wiedeman, Peter Lorraine, Ge Wang
Simulated deep CT characterization of liver metastases with high-resolution filtered back projection reconstruction. Vis. Comput. Ind. Biomed. Art 7(1): 13 (2024) - 2022
- [j15]Jed D. Pack, Mufeng Xu, Ge Wang, Lohendran Baskaran, James Min, Bruno De Man
Cardiac CT blooming artifacts: clinical significance, root causes and potential solutions. Vis. Comput. Ind. Biomed. Art 5(1): 29 (2022) - [j14]Lin Fu
Deep learning tomographic reconstruction through hierarchical decomposition of domain transforms. Vis. Comput. Ind. Biomed. Art 5(1): 30 (2022) - 2021
- [j13]Wenxiang Cong
Monochromatic image reconstruction via machine learning. Mach. Learn. Sci. Technol. 2(2): 25032 (2021) - 2020
- [j12]Ge Wang
Deep learning for tomographic image reconstruction. Nat. Mach. Intell. 2(12): 737-748 (2020) - [j11]Wenxiang Cong, Yan Xi, Paul Fitzgerald, Bruno De Man
Virtual Monoenergetic CT Imaging via Deep Learning. Patterns 1(8): 100128 (2020) - [c3]Fenglei Fan, Sangtae Ahn, Bruno De Man
Deep learning-based model observers that replicate human observers for PET imaging. Image Perception, Observer Performance, and Technology Assessment 2020: 113160E
2010 – 2019
- 2019
- [i1]Lin Fu, Bruno De Man:
A hierarchical approach to deep learning and its application to tomographic reconstruction. CoRR abs/1912.07743 (2019) - 2017
- [j10]Rui Liu, Lin Fu, Bruno De Man, Hengyong Yu
GPU-Based Branchless Distance-Driven Projection and Backprojection. IEEE Trans. Computational Imaging 3(4): 617-632 (2017) - [j9]Lin Fu, Tzu-Cheng Lee, Soo Mee Kim, Adam M. Alessio, Paul E. Kinahan
Comparison Between Pre-Log and Post-Log Statistical Models in Ultra-Low-Dose CT Reconstruction. IEEE Trans. Medical Imaging 36(3): 707-720 (2017) - 2016
- [j8]Yan Xi
High-kVp Assisted Metal Artifact Reduction for X-Ray Computed Tomography. IEEE Access 4: 4769-4776 (2016) - [j7]Lars Gjesteby
Metal Artifact Reduction in CT: Where Are We After Four Decades? IEEE Access 4: 5826-5849 (2016) - [j6]Xiaoyu Tian, Zhye Yin, Bruno De Man
Estimation of Radiation Dose in CT Based on Projection Data. J. Digit. Imaging 29(5): 615-621 (2016) - [j5]Bo Meng, Wenxiang Cong, Yan Xi, Bruno De Man
Energy Window Optimization for X-Ray K-Edge Tomographic Imaging. IEEE Trans. Biomed. Eng. 63(8): 1623-1630 (2016) - 2014
- [j4]Vasile Bogdan Neculaes, Peter M. Edic, Mark Frontera, Antonio Caiafa, Ge Wang
Multisource X-Ray and CT: Lessons Learned and Future Outlook. IEEE Access 2: 1568-1585 (2014) - [c2]Yangyang Yao, Yannan Jin, Paul Fitzgerald, Pete Edic, Zhye Yin, Bruno De Man:
Implementation and validation of the advanced variance estimation technique using CT projection data. ISBI 2014: 1103-1106 - 2010
- [j3]Jonathan Sperl, Dirk Beque, Bernhard Claus, Bruno De Man
Computer-Assisted Scan Protocol and Reconstruction (CASPAR) - Reduction of Image Noise and Patient Dose. IEEE Trans. Medical Imaging 29(3): 724-732 (2010)
2000 – 2009
- 2009
- [j2]Zhye Yin, Bruno De Man
3D Analytic Cone-Beam Reconstruction for Multiaxial CT Acquisitions. Int. J. Biomed. Imaging 2009: 538389:1-538389:11 (2009) - 2006
- [c1]Samit Basu, Bruno De Man
Branchless distance driven projection and backprojection. Computational Imaging 2006: 60650Y - 2001
- [j1]Bruno De Man, Johan Nuyts
An Iterative Maximum-Likelihood Polychromatic Algorithm for CT. IEEE Trans. Medical Imaging 20(10): 999-1008 (2001)
Coauthor Index
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