Open Source

  1. R. Liu, Y. Sun, J. Zhu, L. Tian, and U. S. Kamilov, “Recovery of Continuous 3D Refractive Index Maps from Discrete Intensity-Only Measurements using Neural Fields,” Nat. Mach. Intell., vol. 4, pp. 781–791, September 2022.
    [code] [Project Page] [doi:10.1038/s42256-022-00530-3] [arXiv:2112.00002]
  2. W. Gan, Y. Sun, C. Eldeniz, J. Liu, H. An, and U. S. Kamilov, “Deformation-Compensated Learning for Image Reconstruction without Ground Truth,” IEEE Trans. Med. Imag., vol. 41, no. 9, pp. 2371-2384, September 2022.
    [code] [Project Page] [doi:10.1109/tmi.2022.3163018] [arXiv:2107.05533]
  3. X. Xu, S. V. V. N. Kothapalli, J. Liu, S. Kahali, W. Gan, D. Yablonskiy, and U. S. Kamilov, “Learning-based Motion Artifact Removal Networks for Quantitative R2* Mapping,” Magn. Reson. Med., vol. 88, no. 1, pp. 106-119, 2022.
    [code] [doi:10.1002/mrm.29188] [arXiv:2109.01622]
  4. Y. Sun, J. Liu, M. Xie, B. Wohlberg, and U. S. Kamilov, “CoIL: Coordinate-based Internal Learning for Tomographic Imaging,” IEEE Trans. Comput. Imag., vol. 7, pp. 1400-1412, November 2021.
    [code] [doi:10.1109/tci.2021.3125564] [arXiv:2102.05181]
  5. J. Liu, S. Asif, B. Wohlberg, and U. S. Kamilov, “Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition,” Proc. Ann. Conf. Neural Information Processing Systems (NeurIPS 2021) (December 6-14), pp. 5921-5933.
    [code] [NeurIPS] [arXiv:2106.03668]
  6. 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.
    [code] [doi:10.1109/jstsp.2020.2998402] [arXiv:1912.05854] [supplement]
  7. 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.
    [code] [doi:10.1002/mrm.28344] [arXiv:1912.07087]
  8. Z. Wu, Y. Sun, J. Liu, and U. S. Kamilov, “Online Regularization by Denoising with Applications to Phase Retrieval,” Proc. IEEE Int. Conf. Comp. Vis. Workshops (ICCVW 2019) (Seoul, South Korea, Oct 27 – Nov 2), pp. 3887-3895.
    [code] [doi:10.1109/iccvw.2019.00482] [cvf]
  9. 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.
    [code] [doi:10.1109/lsp.2020.2977214]
  10. Y. Sun, J. Liu, and U. S. Kamilov, Y. Sun, J. Liu, and U. S. Kamilov, “Block Coordinate Regularization by Denoising,” Proc. Ann. Conf. Neural Information Processing Systems (NeurIPS 2019) (Vancouver, Canada, December 8-14), pp. 382-392.
    [code] [NeurIPS:8330]
  11. 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.
    [code] [doi:10.1364/oe.26.014678]
  12. Y. Ma, H. Mansour, D. Liu, P. T. Boufounos, U. S. Kamilov, “Accelerated Image Reconstruction for Nonlinear Diffractive Imaging”, 2017.
    [code] [doi:10.1109/icassp.2018.8462400] [arXiv:1708.01663]
  13. 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.
    [download code] [doi:10.1109/tit.2016.2619373]
  14. 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.
    [download code] [doi:10.1364/optica.2.000517]
  15. 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.
    [download code] [doi:10.1364/josaa.32.001092]
  16. 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.
    [download code] [doi:10.1109/tit.2014.2309005]
  17. 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.
    [download code] [doi:10.1109/tsp.2012.2217334]
  18. U. S. Kamilov, A. Bourquard, A. Amini, and M. Unser, “One-Bit Measurements with Adaptive Thresholds,” IEEE Signal Process. Letters, vol. 19, no. 10., pp. 607–610, October 2012.
    [download code] [doi:10.1109/lsp.2012.2209640]