Journal Articles
2021
- Y. Sun, J. Liu, M. Xie, B. Wohlberg, and U. S. Kamilov, “CoIL: Coordinate-based Internal Learning for Tomographic Imaging,” IEEE Trans. Comput. Imag., in press.
[arXiv:2102.05181]
- C. Eldeniz, W. Gan, S. Chen, T. J. Fraum, D. R. Ludwig, Y. Yan, J. Liu, T. Vahle, U. B. Krishnamurthy, U. S. Kamilov, and H. An, “Phase2Phase: Respiratory Motion-Resolved Reconstruction of Free-Breathing Magnetic Resonance Imaging Using Deep Learning Without a Ground Truth for Improved Liver Imaging,” Invest. Radiol., in press.
[doi:10.1097/rli.0000000000000792]
- Y. Sun, Z. Wu, X. Xu, B. Wohlberg, and U. S. Kamilov, “Scalable Plug-and-Play ADMM with Convergence Guarantees,” IEEE Trans. Comput. Imag., vol. 7, pp. 849-863, July 2021.
[doi:10.1109/tci.2021.3094062] [arXiv:2006.03224]
- J. Liu, Y. Sun, W. Gan, X. Xu, B. Wohlberg, and U. S. Kamilov, “SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees,” IEEE Trans. Comput. Imag., vol. 7, pp. 598-610, June 2021.
[doi:10.1109/tci.2021.3085534] [arXiv:2101.09379]
2020
- Z. Wu, Y. Sun, A. Matlock, J. Liu, L. Tian, and U. S. Kamilov, “SIMBA: Scalable Inversion in Optical Tomography using Deep Denoising Priors,” IEEE J. Sel. Topics Signal Process., vol. 14, no. 6, pp. 1163-1175, October 2020.
[doi:10.1109/jstsp.2020.2999820] [arXiv:1911.13241]
- J. Liu, Y. Sun, C. Eldeniz, W. Gan, H. An, and U. S. Kamilov, “RARE: Image Reconstruction using Deep Priors Learned without Ground Truth,” IEEE J. Sel. Topics Signal Process., vol. 14, no. 6, pp. 1088-1099, October 2020.
[doi:10.1109/jstsp.2020.2998402] [arXiv:1912.05854] [supplement]
- M. Torop, S. Kothapalli, Y. Sun, J. Liu, S. Kahali, D. A. Yablonskiy, and U. S. Kamilov, “Deep learning using a biophysical model for Robust and Accelerated Reconstruction (RoAR) of quantitative and artifact-free R2* images,” Magn. Reson. Med., vol. 84, pp. 2932-2942, 2020.
[doi:10.1002/mrm.28344] [arXiv:1912.07087]
- Y. Sun, J. Liu, and U. S. Kamilov, “Block Coordinate Regularization by Denoising,” IEEE Trans. Comput. Imag., vol. 6, pp. 908-921, 2020.
[doi:10.1109/tci.2020.2996385] [arXiv:1905.05113]
- X. Xu, Y. Sun, J. Liu, B. Wohlberg, and U. S. Kamilov, “Provable Convergence of Plug-and-Play Priors with MMSE denoisers,” IEEE Signal Process. Lett., vol. 27, pp. 1280-1284, 2020.
[doi:10.1109/lsp.2020.3006390] [arXiv:2005.07685]
- G. Song, Y. Sun, J. Liu, Z. Wang, and U. S. Kamilov, “A New Recurrent Plug-and-Play Prior Based on the Multiple Self-Similarity Network,” IEEE Signal Process. Lett., vol. 27, pp. 451-455, 2020.
[doi:10.1109/lsp.2020.2977214] [arXiv:1907.11793]
2019
- Y. Sun, B. Wohlberg, and U. S. Kamilov, “An Online Plug-and-Play Algorithm for Regularized Image Reconstruction,” IEEE Trans. Comput. Imag., vol. 5, no. 3, pp. 395-408, September 2019.
[doi:10.1109/tci.2019.2893568] [arXiv:1809.04693]
- W. Tahir, U. S. Kamilov, and L. Tian, “Holographic particle localization under multiple scattering,” SPIE Adv. Photon., vol. 1, no. 3, p. 036003, May/June 2019.
[doi: 10.1117/1.ap.1.3.036003] [arXiv:1807.11812]
2018
- H. Mansour, D. Liu, U. S. Kamilov, and P. T. Boufounos, “Sparse Blind Deconvolution for Distributed Radar Autofocus Imaging,” IEEE Trans. Comput. Imag., vol. 4, no. 4, pp. 537-551, December 2018.
[doi:10.1109/tci.2018.2875375] [arXiv:1805.03269]
- E. Bostan, U. S. Kamilov, and L. Waller, “Learning-based Image Reconstruction via Parallel Proximal Algorithm,” IEEE Signal Process. Lett., vol. 25, no. 7, pp. 989-993, July 2018.
[doi:10.1109/lsp.2018.2833812] [arXiv:1801.09518]
- Y. Sun, Z. Xia, and U. S. Kamilov, “Efficient and accurate inversion of multiple scattering with deep learning,” Opt. Express, vol. 26, no. 11, pp. 14678-14688, May 2018.
[doi:10.1364/oe.26.014678] [arXiv:1803.06594]
- H.-Y. Liu, D. Liu, H. Mansour, P. T. Boufounos, L. Waller, and U. S. Kamilov, “SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering,” IEEE Trans. Comput. Imag., vol. 4, no. 1, pp. 73-86, March 2018.
[doi:10.1109/tci.2017.2764461] [arXiv:1705.04281]
2017
- U. S. Kamilov, H. Mansour, and B. Wohlberg, “A Plug-and-Play Priors Approach for Solving Nonlinear Imaging Inverse Problems,” IEEE Signal Process. Lett., vol. 24, no. 12, pp. 1872-1876, December 2017.
[doi:10.1109/lsp.2017.2763583]
- U. S. Kamilov and P. T. Boufounos, “Motion-Adaptive Depth Superresolution,” IEEE Trans. Image Process, vol. 26, no. 4, pp. 1723-1731, April 2017.
[doi:10.1109/tip.2017.2658944]
- U. S. Kamilov, “A Parallel Proximal Algorithm for Anisotropic Total Variation Minimization,” IEEE Trans. Image Process., vol. 26, no. 2, pp. 539-548, February 2017.
[doi:10.1109/tip.2016.2629449]
- S. Rangan, A. K. Fletcher, P. Schniter, and U. S. Kamilov, “Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization,” IEEE Trans. Inf. Theory., vol. 63, no. 1, pp. 676-697, January 2017.
[doi:10.1109/tit.2016.2619373] [arXiv:1501.01797]
2016
- U. S. Kamilov, D. Liu, H. Mansour, and P. T. Boufounos, “A Recursive Born Approach to Nonlinear Inverse Scattering,” IEEE Signal Process. Lett., vol. 23, no. 8, pp. 1052-1056, August 2016.
[doi:10.1109/lsp.2016.2579647] [arXiv:1603.03768]
- U. S. Kamilov and H. Mansour, “Learning optimal nonlinearities for iterative thresholding algorithms,” IEEE Signal Process. Lett., vol. 23, no. 5, pp. 747–751, May 2016.
[doi:10.1109/lsp.2016.2548245] [arXiv:1512.04754]
- U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh, A. Goy, C. Vonesch, M. Unser, and D. Psaltis, “Optical tomographic image reconstruction based on beam propagation and sparse regularization,” IEEE Trans. Comput. Imag., vol. 2, no. 1, pp. 59–70, March 2016.
[doi:10.1109/tci.2016.2519261]
2015
- U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh, A. Goy, C. Vonesch, M. Unser, and D. Psaltis,
“Learning Approach to Optical Tomography,” Optica, vol. 2, no. 6, pp. 517–522, June 2015.
[doi:10.1364/optica.2.000517] [Nature “News and Views”]
- U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh, D. Psaltis, and M. Unser, “Isotropic inverse-problem approach for two-dimensional phase unwrapping,” J. Opt. Soc. Am. A, vol. 32, no. 6, pp. 1092–1100, June 2015.
[doi:10.1364/josaa.32.001092] [arXiv:1503.04744]
2014
- U. S. Kamilov, E. Bostan, and M. Unser, “Variational Justification of Cycle Spinning for Wavelet-Based Solutions of Inverse Problems,” IEEE Signal Process. Lett., vol. 21, no. 11, pp. 1326–1330, November 2014.
[doi:10.1109/lsp.2014.2334306]
- U. S. Kamilov, S. Rangan, A. K. Fletcher, and M. Unser, “Approximate Message Passing with Consistent Parameter Estimation and Application to Sparse Learning,” IEEE Trans. Inf. Theory, vol. 60, no. 5, pp. 2969–2985, May 2014.
[doi:10.1109/tit.2014.2309005]
2013
- E. Bostan, U. S. Kamilov, M. Nilchian, and M. Unser, “Sparse Stochastic Processes and Discretization of Linear Inverse Problems,” IEEE Trans. Image Process., vol. 22, no. 7, pp. 2699–2710, July 2013.
[doi:10.1109/tip.2013.2255305]
- A. Kazerouni, U. S. Kamilov, E. Bostan, and M. Unser, “Bayesian Denoising: From MAP to MMSE Using Consistent Cycle Spinning,” IEEE Signal Process. Lett., vol. 20, no. 3, pp. 249–252, March 2013.
[doi:10.1109/lsp.2013.2242061]
- A. Amini, U. S. Kamilov, E. Bostan, and M. Unser, “Bayesian Estimation for Continuous-Time Sparse Stochastic Processes,” IEEE Trans. Signal Process., vol. 61, no. 4, pp. 907–920, February 2013.
[doi:10.1109/tsp.2012.2226446]
- U. S. Kamilov, P. Pad, A. Amini, and M. Unser, “MMSE Estimation of Sparse Lévy Processes,” IEEE Trans. Signal Process., vol. 61, no. 10, pp. 137–147, January 2013.
[doi:10.1109/tsp.2012.2222394]
2012
- U. S. Kamilov, V. K. Goyal, and S. Rangan, “Message-Passing De-Quantization with Applications to Compressed Sensing,” IEEE Trans. Signal Process., vol. 60, no. 12, pp. 6270–6281, December 2012.
[doi:10.1109/tsp.2012.2217334] [arXiv:1105.6368] [IEEE SPS Best Paper Award 2017]
- U. S. Kamilov, A. Bourquard, A. Amini, and M. Unser, “One-Bit Measurements with Adaptive Thresholds,” IEEE Signal Process. Lett., vol. 19, no. 10., pp. 607–610, October 2012.
[doi:10.1109/lsp.2012.2209640]
- U. S. Kamilov, E. Bostan, and M. Unser, “Wavelet Shrinkage with Consistent Cycle Spinning Generalizes Total Variation Denoising,” IEEE Signal Process. Lett., vol. 19, no. 4, pp. 187–190, April 2012.
[doi:10.1109/lsp.2012.2185929]
