Michael Kellman
Michael Kellman
University of California, San Francisco
Verified email at berkeley.edu - Homepage
Title
Cited by
Cited by
Year
Physics-based learned design: optimized coded-illumination for quantitative phase imaging
MR Kellman, E Bostan, NA Repina, L Waller
IEEE Transactions on Computational Imaging 5 (3), 344-353, 2019
792019
Deep phase decoder: self-calibrating phase microscopy with an untrained deep neural network
E Bostan, R Heckel, M Chen, M Kellman, L Waller
Optica 7 (6), 559-562, 2020
332020
Data-Driven Design for Fourier Ptychographic Microscopy
M Kellman, E Bostan, M Chen, L Waller
International Conference on Computational Photography, 2019
302019
Barker-Coded Node-Pore Resistive Pulse Sensing With Built-in Coincidence Correction
M Kellman, F Rivest, A Pechacek, L Sohn, M Lustig
42nd IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017
132017
Node-Pore Coded Coincidence Correction: Coulter Counters, Code Design, and Sparse Deconvolution
M Kellman, F Rivest, A Pechacek, L Sohn, M Lustig
IEEE Sensors Journal, 2018
122018
Memory-efficient learning for large-scale computational imaging
M Kellman, K Zhang, E Markley, J Tamir, E Bostan, M Lustig, L Waller
IEEE Transactions on Computational Imaging 6, 1403-1414, 2020
112020
Motion-resolved quantitative phase imaging
M Kellman, M Chen, ZF Phillips, M Lustig, L Waller
Biomedical optics express 9 (11), 5456-5466, 2018
92018
How to do physics-based learning
M Kellman, M Lustig, L Waller
arXiv preprint arXiv:2005.13531, 2020
12020
Robust Multi-Pitch Tracking: a trained classifier based approach
M Kellman, N Morgan
International Computer Science Institute, 2016
12016
Memory-efficient Learning for High-Dimensional MRI Reconstruction
K Wang, M Kellman, CM Sandino, K Zhang, SS Vasanawala, JI Tamir, ...
arXiv preprint arXiv:2103.04003, 2021
2021
Algorithmic self-calibration for optimized 3D quantitative differential phase contrast microscopy
R Cao, M Kellman, DY Ren, R Eckert, L Waller
Quantitative Phase Imaging VII 11653, 116530R, 2021
2021
3D Differential Phase Contrast Microscopy with Axial Motion Deblurring
R Cao, M Kellman, D Ren, L Waller
Computational Optical Sensing and Imaging, CF4C. 2, 2020
2020
Data-driven experimental design for computational imaging (Conference Presentation)
MR Kellman, E Bostan, M Lustig, L Waller
Quantitative Phase Imaging VI 11249, 1124916, 2020
2020
3D fluorescence deconvolution with deep priors (Conference Presentation)
K Zhang, MR Kellman, E Bostan, L Waller
Three-Dimensional and Multidimensional Microscopy: Image Acquisition and …, 2020
2020
Physics-based learning for measurement diversity in 3D refractive index microscopy (Conference Presentation)
R Eckert, MR Kellman, L Waller
Three-Dimensional and Multidimensional Microscopy: Image Acquisition and …, 2020
2020
Physics-based Learning for Large-scale Computational Imaging
MR Kellman
PQDT-Global, 2020
2020
Memory-efficient Learning for Large-scale Computational Imaging--NeurIPS deep inverse workshop
M Kellman, J Tamir, E Boston, M Lustig, L Waller
arXiv preprint arXiv:1912.05098, 2019
2019
Characterizing the feeding current of sessile microorganisms using digital holography
M Wells, J Deloya Garcia, S Chowdhury, M Kellman, L Waller, R Pepper
APS Division of Fluid Dynamics Meeting Abstracts, NP05. 082, 2019
2019
Motion resolved quantitative phase imaging (Conference Presentation)
MR Kellman, ZF Phillips, D Ren, M Lustig, L Waller
Computational Imaging III 10669, 106690D, 2018
2018
Node-Pore Coded Coincidence Correcting Microfluidic Channel Framework: Code Design and Sparse Deconvolution
M Kellman, M Lustig
2017
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