Publications

You can also find my articles on my Semantic Scholar Profile.

Preprints

  1. A Sriram, MJ Muckley, K Sinha, F Shamout, J Pineau, KJ Geras, L Azour, Y Aphinyanaphongs, N Yakubova, W Moore. COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction. arXiv preprint arXiv:2101.04909, 2021. [Preprint PDF]
  2. J Zbontar, F Knoll, A Sriram, T Murrell, Z Huang, MJ Muckley, A Defazio, R Stern, P Johnson, M Bruno, et al. fastMRI: An open dataset and benchmarks for accelerated MRI. arXiv preprint arXiv:1811.08839, 2018. [Preprint PDF]

Journal Articles

  1. MJ Muckley, B Riemenschneider, A Radmanesh, S Kim, G Jeong, J Ko, Y Jun, H Shin, D Hwang, M Mostapha, et al. Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction. IEEE Transactions on Medical Imaging, 2021. In press. [PDF]
  2. MJ Muckley, B Ades-Aron, A Papaioannou, G Lemberskiy, E Solomon, YW Lui, DK Sodickson, E Fieremans, DS Novikov, F Knoll. Training a neural network for Gibbs and noise removal in diffusion MRI. Magnetic Resonance in Medicine, 85(1):413–428, 2021. [Preprint PDF]
  3. F Knoll, T Murrell, A Sriram, N Yakubova, J Zbontar, M Rabbat, A Defazio, MJ Muckley, DK Sodickson, CL Zitnick, MP Recht. Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge. Magnetic Resonance in Medicine, 84(6):3054–3070, 2020. [Preprint PDF]
  4. MP Recht, J Zbontar, DK Sodickson, F Knoll, N Yakubova, A Sriram, T Murrell, A Defazio, M Rabbat, L Rybak, et al. Using deep learning to accelerate knee MRI at 3 T: Results of an interchangeability study. American Journal of Roentgenology, 215(6):1421–1429, 2020.
  5. F Knoll, J Zbontar, A Sriram, MJ Muckley, M Bruno, A Defazio, M Parente, KJ Geras, Joe Katsnelson, H Chandarana, et al. fastMRI: A publicly available raw k-spaceand DICOM dataset of knee images for accelerated MR image reconstruction using machine learning. Radiology: Artificial Intelligence, 2(1):e190007, 2020.
  6. T Chitiboi, M Muckley, B Dane, C Huang, L Feng, H Chandarana. Pancreas deformation in the presence of tumors using feature tracking from free-breathing XD-GRASP MRI. Journal of Magnetic Resonance Imaging, 50(5):1633–1640, 2019.
  7. MJ Muckley, B Chen, T Vahle, T O’Donnell, F Knoll, AD Sodickson, DK Sodickson, R Otazo. Image reconstruction for interrupted-beam x-ray CT on diagnostic clinical scanners. Physics in Medicine and Biology, 64(15):155007, 2019. [PDF]
  8. B Chen, E Kobler, MJ Muckley, AD Sodickson, T O’Donnell, T Flohr, B Schmidt, DK Sodickson, R Otazo. SparseCT: System concept and design of multislit collimators. Medical Physics, 46(6):2589–2599, 2019.
  9. MA Cauble, MJ Muckley, M Fang, JA Fessler, K Welch, ED Rothman, BG Orr, LT Duong, MMB Holl. Estrogen depletion and drug treatment alter the microstructure of type I collagen in bone. Bone Reports, 5:243–251, 2016. [PDF]
  10. MJ Muckley, DC Noll, JA Fessler. Fast parallel MR image reconstruction via B1-based, adaptive restart, iterative soft thresholding algorithms (BARISTA). IEEE Transactions on Medical Imaging, 34(2):578–588, 2015. [Preprint PDF]
  11. Z Zhong, M Muckley, S Agcaoglu, ME Grisham, H Zhao, M Orth, MS Lilburn, O Akkus, DM Karcher. The morphological, material-level, and ash properties of turkey femurs from 3 different genetic strains during production. Poultry Science, 91(11):2736–2746, 2012. [PDF]
  12. Z Xu, X Sun, J Liu, Q Song, M Muckley, O Akkus, YL Kim. Spectroscopic visualization of nanoscale deformation in bone: interaction of light with partially disordered nanostructure. Journal of Biomedical Optics, 15(6):060503, 2010. [PDF]

High-Impact Conference Articles

  1. Z Zhang, A Romero, MJ Muckley, P Vincent, L Yang, M Drozdzal. Reducing uncertainty in undersampled MRI reconstruction with active acquisition. In CVPR, pages 2049–2058, 2019. [PDF]

Conference Papers

Workshop and 4-page proceedings papers.

  1. S Gong, M Muckley, N Wu, T Makino, GS Kim, L Heacock, L Moy, F Knoll, KJ Geras. Large-scale classification of breast MRI exams using deep convolutional networks. In Medical Imaging Meets NeurIPS Workshop, 2019. [PDF]
  2. PM Johnson, MJ Muckley, M Bruno, E Kobler, K Hammernik, T Pock, F Knoll. Joint multi-anatomy training of a variational network for reconstruction of accelerated magnetic resonance image acquisitions. In MICCAI Recon Workshop, pages 71–79, 2019.
  3. MJ Muckley, B Chen, T O’Donnell, M Berner, T Allmendinger, K Stierstorfer, T Flohr, B Schmidt, A Sodickson, D Sodickson, R Otazo. Reconstruction of reduced-dose SparseCT data acquired with an interruped-beam prototype on a clinical scanner. In CT Meeting, pages 56–59, 2018. [PDF]
  4. B Chen, MJ Muckley, A Sodickson, T O’Donnell, M Berner, T Allmendinger, K Stierstorfer, T Flohr, B Schmidt, D Sodickson, R Otazo. First multislit collimator prototype for SparseCT: design, manufacturing and initial validation. In CT Meeting, pages 52–55, 2018. [PDF]
  5. E Kobler, MJ Muckley, B Chen, F Knoll, K Hammernik, T Pock, DK Sodickson, R Otazo. Variational network learning for low-dose CT. In CT Meeting, pages 430–434, 2018. [PDF]
  6. E Kobler, M Muckley, B Chen, F Knoll, K Hammernik, T Pock, D Sodickson, R Otazo. Variational deep learning for low-dose computed tomography. In ICASSP, pages 6687–6691, 2018.
  7. B Chen, M Muckley, A Sodickson, T O’Donnell, F Knoll, D Sodickson, R Otazo. Evaluation of SparseCT on patient data using realistic undersampling models. In SPIE Medical Imaging, volume 10573, page 1057342, 2018.
  8. M Muckley, B Chen, T Vahle, F Knoll, A Sodickson, DK Sodickson, R Otazo. Regularizer performance for SparseCT image reconstruction with practical subsampling. In Fully3D, pages 572–575, 2017. [PDF]
  9. B Chen, MJ Muckley, T O’Donnell, A Sodickson, T Flohr, K Stierstorfer, B Schmidt, F Knoll, A Primak, D Faul, et al. Realistic undersampling model for compressed sensing using a multi-slit collimator. In Fully3D, pages 314–317, 2017. [PDF]
  10. MJ Muckley, JA Fessler. Fast MR image reconstruction with orthogonal wavelet regularization via shift-variant shrinkage. In ICIP, pages 3651–3655, 2014. [PDF]

Conference Abstracts

  1. B Riemenschneider, MJ Muckley, A Radmanesh, S Kim, G Jeong, J Ko, Y Jun, H Shin, D Hwang, M Mostapha, et al. Results of the 2020 fastMRI brain reconstruction challenge. In Proceedings of the International Society for Magnetic Resonance in Medicine, page 63, 2021.
  2. MJ Muckley, T Murrell, S Booshan, H Chandarana, F Knoll, DK Sodickson. Unsupervised reconstruction of continuous dynamic radial acquisitions via CNN-NUFFT self-consistency. In ISMRM, 2020.
  3. T Murrell, MJ Muckley, F Knoll, H Chandarana, DK Sodickson. Self-supervised dynamic MR image reconstruction with a sequence-to-sequence NUFFT-CNN. In ISMRM Data Sampling & Image Reconstruction Workshop, 2020.
  4. MJ Muckley, R Stern, T Murrell, F Knoll. TorchKbNufft: A high-level, hardware-agnostic non-uniform fast Fourier transform. In ISMRM Data Sampling & Image Reconstruction Workshop, 2020.
  5. MJ Muckley, A Papaioannou, B Ades-Aron, DK Sodickson, YW Lui, E Fieremans, DS Novikov, F Knoll. Learned Gibbs removal in partial Fourier acquisitions for diffusion MRI. In ISMRM, page 3402, 2019.
  6. MJ Muckley, A Papaioannou, B Ades-Aron, DK Sodickson, YW Lui, E Fieremans, DS Novikov, F Knoll. Improving mean kurtosis measurements in diffusion MRI via learned Gibbs removal. In ISMRM Machine Learning Workshop, Part 2, 2018.
  7. MJ Muckley, JA Fessler, MVW Zibetti. Accelerating non-Cartesian, sparsity-promoting image reconstruction via line search FISTA. In ISMRM, page 2809, 2018. [PDF]
  8. MJ Muckley, L Feng, H Chandarana, DK Sodickson, R Otazo. Respiratory motion-field reconstruction using low-rank plus sparse (L+S) approach for dynamic MRI of the lungs. In ISMRM, page 3864, 2017.
  9. R Ramb, M Zenge, L Feng, MJ Muckley, C Forman, L Axel, DK Sodickson, R Otazo. Low-rank plus sparse tensor reconstruction for high-dimensional cardiac MRI. In ISMRM, page 1199, 2017.
  10. MJ Muckley, DC Noll, JA Fessler. Fast, iterative subsampled spiral reconstruction via circulant majorizers. In ISMRM, page 521, 2016.
  11. MJ Muckley, DC Noll, JA Fessler. Majorizer design for non-Cartesian MRI with sparsity-promoting regularization. In ISMRM Data Sampling & Image Reconstruction Workshop, 2016. [PDF]
  12. MJ Muckley, DC Noll, JA Fessler. Momentum optimization for iterative shrinkage algorithms in parallel MRI with sparsity-promoting regularization. In ISMRM, page 3413, 2015.
  13. MJ Muckley, Douglas C. Noll, and Jeffrey A. Fessler. Accelerating SENSE-type MR image reconstruction algorithms with incremental gradients. In ISMRM, page 4400, 2014. [PDF]
  14. MJ Muckley, SJ Peltier, DC Noll, JA Fessler. Model-based reconstruction for physiological noise correction in functional MRI. In ISMRM, page 2623, 2013. [PDF]
  15. MJ Muckley, SJ Peltier, JA Fessler, DC Noll. Group sparsity reconstruction for physiological noise correction in functional MRI. In ISMRM Data Sampling & Image Reconstruction Workshop, 2013. [PDF]
  16. M Muckley, S Agcaoglu, Z Zhong, H Zhao, M Grisham, D Karcher, M Orth, M Lilburn, O Akkus. The effect of selective breeding for body weight on geometric properties in turkey femurs. In ASME, pages 901–902, 2011.
  17. Z Zhong, S Agcaoglu, M Muckley, H Zhao, D Karcher, M Orth, M Lilburn, O Akkus. Changes in turkey femora mechanical properties resulting from selective breeding for body weight. In ASME, pages 897–898, 2011.