Technical Reports, Etc.

  1. A O Hero, J A Fessler.
    Asymptotic convergence properties of EM-type algorithms.
    Technical Report 282, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Apr. 1993.
  2. J A Fessler, A O Hero.
    Space-alternating generalized EM algorithms for penalized maximum-likelihood image reconstruction.
    Technical Report 286, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Feb. 1994.
  3. J A Fessler.
    EM and gradient algorithms for transmission tomography with background contamination.
    Technical Report UM-PET-JF-94-1, Cyclotron PET Facility, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Dec. 1994.
  4. J A Fessler.
    ASPIRE 3.0 user's guide: A sparse iterative reconstruction library.
    Technical Report 293, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Jul. 1995.
  5. J A Fessler.
    Resolution properties of regularized image reconstruction methods.
    Technical Report 297, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Aug. 1995.
  6. J A Fessler, J M Ollinger.
    Signal processing pitfalls in positron emission tomography.
    Technical Report 302, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Sep. 1996.
  7. A O Hero, M Usman, A Sauve, J A Fessler.
    Recursive algorithms for computing the Cramer-Rao bound.
    Technical Report 305, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Nov. 1996.
  8. J A Fessler.
    Conjugate-gradient preconditioning methods: numerical results.
    Technical Report 303, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Jan. 1997.
  9. J A Fessler.
    Spatial resolution properties of penalized weighted least-squares image reconstruction with model mismatch.
    Technical Report 308, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Mar. 1997.
  10. J A Fessler.
    Users guide for ASPIRE 3D image reconstruction software.
    Technical Report 310, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Jul. 1997.
  11. J A Fessler.
    On transformations of random vectors.
    Technical Report 314, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Aug. 1998.
  12. J A Fessler.
    Computing parametric images from dynamic sequences using a QR decomposition method.
    Technical Report 321, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Dec. 1998.
  13. J A Fessler.
    Some tips for LaTeX, Matlab, and ANSI C.
    Technical Report ?, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Nov. 2001.
    Script mentioned in report.
  14. J A Fessler.
    Iterative tomographic image reconstruction using nonuniform fast Fourier transforms.
    Technical Report ?, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Dec. 2001.
  15. S Ahn, J A Fessler.
    Standard errors of mean, variance, and standard deviation estimators.
    Technical Report 413, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Jul. 2003.
  16. S Matej, J A Fessler, I G Kazantsev.
    Fourier-based forward and back-projectors for iterative image reconstruction.
    Technical Report MIPG303, MIPG Technical Report, University of Pennsylvania, May. 2003.
  17. M W Jacobson, J A Fessler.
    Properties of MM algorithms on convex feasible sets: extended version.
    Technical Report 353, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Nov. 2004.
  18. Dan Ruan, J A Fessler.
    Adaptive ellipse tracking and a convergence proof.
    Technical Report 382, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, May. 2007.
  19. Dan Ruan, J A Fessler.
    Fundamental performance analysis in image registration problems: \Cramer-Rao bound and its variations.
    Technical Report 386, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Mar. 2008.
  20. Daniel J Lingenfelter, J A Fessler.
    System modeling for gamma-ray imaging systems.
    Technical Report 411, Comm. and Sign. Proc. Lab., Dept. of EECS, Univ. of Michigan, Ann Arbor, MI, 48109-2122, Mar. 2012.

Dissertation

  1. J A Fessler.
    Object-based 3-D reconstruction of arterial trees from a few projections. Stanford Univ., 1990

Software

  1. J A Fessler.
    Michigan image reconstruction toolbox (MIRT) for Matlab.
    Available from \myurl., 2016
  2. J A Fessler.
    Matlab tomography toolbox.
    Available from \myurl., 2004
  3. Alfredo Iusem, Sergio Furuie, Elias S Helou, Eduardo X Miqueles, J A Fessler, Marcelo V W Zibetti, Antonio \Leitao, Ana Gabriela Martinez, Russell Luke, Thomas Katsekpor, Jose Mario Martinez.
    South-American adventures from kayak to inverse problems: A tribute to Alvaro Rodolfo De Pierro. 2025

ARXIV papers

  1. Rodrigo A Lobos, Javier Salazar Cavazos, Raj Rao Nadakuditi, J A Fessler.
    Smooth optimization algorithms for global and locally low-rank regularizers. 2025
  2. Tao Hong, Zhaoyi Xu, Se Young Chun, Luis Hernandez-Garcia, J A Fessler.
    Convergent complex quasi-Newton proximal method for gradient-driven denoisers in compressed sensing MRI reconstruction. 2025
  3. Hongze Yu, J A Fessler, Yun Jiang.
    Bilevel optimized implicit neural representation for scan-specific accelerated MRI reconstruction. 2025
  4. Siddhant Gautam, Angqi Li, Nicole Seiberlich, J A Fessler, Saiprasad Ravishankar.
    Scan-adaptive MRI undersampling using neighbor-based optimization (SUNO). 2025
  5. Siyi Chen, Yixuan Jia, Qing Qu, He Sun, J A Fessler.
    FlowDAS: A flow-based framework for data assimilation. 2025
  6. Tao Hong, Zhaoyi Xu, Jason Hu, J A Fessler.
    On adapting randomized \Nystrom preconditioners to accelerate variational image reconstruction. 2024
  7. Jason Hu, Bowen Song, J A Fessler, Liyue Shen.
    Patch-based diffusion models beat whole-image models for mismatched distribution inverse problems. 2024
  8. Xiaojian Xu, Marc Klasky, Michael T McCann, Jason Hu, J A Fessler.
    Swap-Net: A memory-efficient 2.5D network for sparse-view 3D cone beam CT reconstruction. 2024
  9. Bowen Song, Jason Hu, Zhaoxu Luo, J A Fessler, Liyue Shen.
    DiffusionBlend: learning 3D image prior through position-aware diffusion score blending for 3D computed tomography reconstruction. 2024
  10. Jason Hu, Bowen Song, Xiaojian Xu, Liyue Shen, J A Fessler.
    Learning image priors through patch-based diffusion models for solving inverse problems. 2024
  11. Tao Hong, Xiaojian Xu, Jason Hu, J A Fessler.
    Provable preconditioned plug-and-play approach for compressed sensing MRI reconstruction. 2024
  12. Kyle Gilman, David Hong, J A Fessler, Laura Balzano.
    Streaming probabilistic PCA for missing data with heteroscedastic noise. 2023
  13. Javier Antonio Salazar Cavazos, J A Fessler, Laura Balzano.
    ALPCAH: Sample-wise heteroscedastic PCA with tail singular value regularization. 2023
  14. Jonathan Schwartz, Zichao Wendy Di, Yi Jiang, Jason Manassa, Jacob Pietryga, Yi-wen Qian, Mingee Cho, Jonathan Rowell, Huihuo Zheng, Richard Robinson, Junsi Gu, Steve Rozeveld, Peter Ercius, J A Fessler, Ting Xu, Mary C Scott, Robert Hovden.
    Imaging 3D chemistry at 1 nm resolution with fused multi-modal electron tomography. 2023
  15. Zongyu Li, Jason Hu, Xiaojian Xu, Liyue Shen, J A Fessler.
    Poisson-Gaussian holographic phase retrieval with score-based image prior. 2023
  16. Cameron J Blocker, Haroon Raja, J A Fessler, Laura Balzano.
    Dynamic subspace estimation with Grassmannian geodesics. 2023
  17. Tao Hong, Luis Hernandez, J A Fessler.
    A complex quasi-Newton proximal method for image reconstruction in compressed sensing MRI. 2023
  18. Guanhua Wang, Douglas C Noll, J A Fessler.
    Adaptive sampling for linear sensing systems via Langevin dynamics. 2023
  19. Alec S Xu, Laura Balzano, J A Fessler.
    HeMPPCAT: mixtures of probabilistic principal component analysers for data with heteroscedastic noise. 2023
  20. Zongyu Li, Yuni K Dewaraja, J A Fessler.
    Training end-to-end unrolled iterative neural networks for SPECT image reconstruction. 2023
  21. Guanhua Wang, Jon-Fredrik Nielsen, J A Fessler, Douglas C Noll.
    Stochastic optimization of 3D non-Cartesian sampling trajectory (SNOPY). 2022
  22. Jonathan Schwartz, Zichao Wendy Di, Yi Jiang, Alyssa J Fielitz, Don-Hyung Ha, Sanjaya D Perera, Ismail El Baggari, Richard D Robinson, J A Fessler, Colin Ophus, Steve Rozeveld, Robert Hovden.
    Imaging atomic-scale chemistry from fused multi-modal electron microscopy. 2022
  23. Anish Lahiri, Marc L Klasky, J A Fessler, Saiprasad Ravishankar.
    Sparse-view cone beam CT reconstruction using data-consistent supervised and adversarial learning from scarce training data. 2022
  24. Guanhua Wang, J A Fessler.
    Efficient approximation of Jacobian matrices involving a non-uniform fast Fourier transform (NUFFT). 2021
  25. Caroline Crockett, J A Fessler.
    Bilevel methods for image reconstruction. 2021
  26. Shouchang Guo, J A Fessler, Douglas C Noll.
    Manifold model for high-resolution fMRI joint reconstruction and dynamic quantification. 2021
  27. Anish Lahiri, Guanhua Wang, Saiprasad Ravishankar, J A Fessler.
    Blind primed supervised (BLIPS) learning for MR image reconstruction. 2021
  28. Zongyu Li, Kenneth Lange, J A Fessler.
    Algorithms for Poisson phase retrieval. 2021
  29. Guanhua Wang, Tianrui Luo, Jon-Fredrik Nielsen, Douglas C Noll, J A Fessler.
    B-spline parameterized joint optimization of reconstruction and k-space trajectories (BJORK) for accelerated 2D MRI. 2021
  30. David Hong, Kyle Gilman, Laura Balzano, J A Fessler.
    HePPCAT: probabilistic PCA for data with heteroscedastic noise. 2021
  31. Tianrui Luo, Douglas C Noll, J A Fessler, Jon-Fredrik Nielsen.
    Joint design of RF and gradient waveforms via auto-differentiation for 3D tailored excitation in MRI. 2020
  32. Claire Yilin Lin, J A Fessler.
    Efficient regularized field map estimation in 3D parallel MRI. 2020
  33. Xuehang Zheng, Il Yong Chun, Yong Long, J A Fessler.
    BCD-net for low-dose CT reconstruction: Acceleration, convergence, and generalization. 2019
  34. Il Yong Chun, Zhengyu Huang, Hongki Lim, J A Fessler.
    Momentum-Net: Fast and convergent iterative neural network for inverse problems. 2019
  35. Hongki Lim, Il Yong Chun, Yuni K Dewaraja, J A Fessler.
    Improved low-count quantitative PET reconstruction with a variational neural network. 2019
  36. Anish Lahiri, J A Fessler, Luis Hernandez-Garcia.
    Optimizing MRF-ASL scan design for precise quantification of brain hemodynamics using neural network regression. 2019
  37. Sai Ravishankar, Jong Chul Ye, J A Fessler.
    Image reconstruction: from sparsity to data-adaptive methods and machine learning. 2019
  38. Greg Ongie, Naveen Murthy, Laura Balzano, J A Fessler.
    A memory-efficient algorithm for large-scale sparsity regularized image reconstruction. 2019
  39. J A Fessler.
    Optimization methods for MR image reconstruction. 2019
  40. Il Yong Chun, David Hong, Ben Adcock, J A Fessler.
    Convolutional analysis operator learning: Dependence on training data. 2019
  41. Zhipeng Li, Saiprasad Ravishankar, Yong Long, J A Fessler.
    DECT-MULTRA: dual-energy CT image decomposition with learned mixed material models and efficient clustering. 2019
  42. Madison G McGaffin, Hao Chen, J A Fessler, Volker Sick.
    A practical light transport system model for chemiluminescence distribution reconstruction. 2018
  43. David Hong, Fan Yang, J A Fessler, Laura Balzano.
    Optimally weighted PCA for high-dimensional heteroscedastic data. 2018
  44. Gopal Nataraj, Jon-Fredrik Nielsen, Mingjie Gao, J A Fessler.
    Fast, precise myelin water quantification using DESS MRI and kernel learning.
    Submitted., 2018
  45. Brian E Moore, Saiprasad Ravishankar, Raj Rao Nadakuditi, J A Fessler.
    Online adaptive image reconstruction (OnAIR) using dictionary models. 2018
  46. Siqi Ye, Saiprasad Ravishankar, Yong Long, J A Fessler.
    SPULTRA: low-dose CT image reconstruction with joint statistical and learned image models. 2018
  47. Donghwan Kim, J A Fessler.
    Optimizing the efficiency of first-order methods for decreasing the gradient of smooth convex functions. 2018
  48. Il Yong Chun, J A Fessler.
    Deep BCD-net using identical encoding-decoding CNN structures for iterative image recovery. 2018
  49. Il Yong Chun, J A Fessler.
    Convolutional analysis operator learning: acceleration and convergence. 2018
  50. Qiaoqiao Ding, Yong Long, Xiaoqun Zhang, J A Fessler.
    Statistical image reconstruction using mixed Poisson-Gaussian noise model for X-ray CT. 2018
  51. Xuehang Zheng, Il Yong Chun, Zhipeng Li, Yong Long, J A Fessler.
    Sparse-view X-ray CT reconstruction using $\ell_1$ prior with learned transform. 2017
  52. Gopal Nataraj, Jon-Fredrik Nielsen, Clayton Scott, J A Fessler.
    Dictionary-free MRI PERK: Parameter estimation via regression with kernels. 2017
  53. J A Fessler.
    Medical image reconstruction: a brief overview of past milestones and future directions. 2017
  54. Xuehang Zheng, Zening Lu, Saiprasad Ravishankar, Yong Long, J A Fessler.
    Low dose CT image reconstruction with learned sparsifying transform. 2017
  55. Il Yong Chun, J A Fessler.
    Convolutional dictionary learning: acceleration and convergence. 2017
  56. Xuehang Zheng, Saiprasad Ravishankar, Yong Long, J A Fessler.
    PWLS-ULTRA: An efficient clustering and learning-based approach for low-dose 3D CT image reconstruction. 2017
  57. David Hong, Laura Balzano, J A Fessler.
    Asymptotic performance of PCA for high-dimensional heteroscedastic data. 2017
  58. Donghwan Kim, J A Fessler.
    Adaptive restart of the optimized gradient method for convex optimization. 2017
  59. Saiprasad Ravishankar, Brian E Moore, Raj Rao Nadakuditi, J A Fessler.
    Low-rank and adaptive sparse signal (LASSI) models for highly accelerated dynamic imaging. 2016
  60. David Hong, Laura Balzano, J A Fessler.
    Towards a theoretical analysis of PCA for heteroscedastic data. 2016
  61. Donghwan Kim, J A Fessler.
    Fast dual proximal gradient algorithms with rate $O(1/k^{1.5})$ for convex minimization. 2016
  62. Donghwan Kim, J A Fessler.
    Another look at the fast iterative shrinkage/thresholding algorithm (FISTA). 2016
  63. Donghwan Kim, J A Fessler.
    Generalizing the optimized gradient method for smooth convex minimization. 2016
  64. Donghwan Kim, J A Fessler.
    Optimized first-order methods for smooth convex minimization - Supplementary material. 2015
  65. Hung Nien, J A Fessler.
    Relaxed linearized algorithms for faster X-ray CT image reconstruction. 2015
  66. Saiprasad Ravishankar, Raj Rao Nadakuditi, J A Fessler.
    Efficient sum of outer products dictionary learning (SOUP-DIL) - The $\ell_0$ method. 2015
  67. Saiprasad Ravishankar, Raj Rao Nadakuditi, J A Fessler.
    Efficient sum of outer products dictionary learning (SOUP-DIL) and its application to inverse problems. 2017
  68. Donghwan Kim, J A Fessler.
    On the convergence analysis of the optimized gradient methods. 2015
  69. Madison G McGaffin, J A Fessler.
    Algorithmic design of majorizers for large-scale inverse problems. 2015
  70. Daniel S Weller, Ayelet Pnueli, Gilad Divon, Ori Radzyner, Yonina C Eldar, J A Fessler.
    Undersampled phase retrieval with outliers. 2014
  71. Donghwan Kim, J A Fessler.
    Optimized first-order methods for smooth convex minimization. 2014
  72. Hung Nien, J A Fessler.
    Fast X-ray CT image reconstruction using the linearized augmented Lagrangian method with ordered subsets. 2014
  73. Hung Nien, J A Fessler.
    A convergence proof of the split Bregman method for regularized least-squares problems. 2014
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