MRI Reconstruction Using Deep Bayesian Estimation

MRI Reconstruction Using Deep Bayesian Estimation

3 September 2019

Papers citing "MRI Reconstruction Using Deep Bayesian Estimation"

13 / 13 papers shown

Title
Diffusion Probabilistic Generative Models for Accelerated, in-NICU Permanent Magnet Neonatal MRI Yamin Arefeen Brett Levac Bhairav Patel Chang Ho Jonathan I. Tamir DiffM MedIm 53 0 0 21 May 2025
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI Jure Zbontar Florian Knoll Anuroop Sriram Tullie Murrell Zhengnan Huang ... Erich Owens C. L. Zitnick M. Recht D. Sodickson Yvonne W. Lui OOD 65 843 0 21 Nov 2018
Distribution Matching in Variational Inference Mihaela Rosca Balaji Lakshminarayanan S. Mohamed GAN CML DRL 56 98 0 19 Feb 2018
MoDL: Model Based Deep Learning Architecture for Inverse Problems H. Aggarwal M. Mani M. Jacob 110 1,016 0 07 Dec 2017
MR image reconstruction using deep density priors K. Tezcan Christian F. Baumgartner R. Luechinger K. Pruessmann E. Konukoglu 52 137 0 30 Nov 2017
A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction Jo Schlemper Jose Caballero Joseph V. Hajnal Anthony N. Price Daniel Rueckert 74 1,128 0 08 Apr 2017
Learning a Variational Network for Reconstruction of Accelerated MRI Data Kerstin Hammernik Teresa Klatzer Erich Kobler M. Recht D. Sodickson Thomas Pock Florian Knoll 48 1,539 0 03 Apr 2017
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications Tim Salimans A. Karpathy Xi Chen Diederik P. Kingma 75 939 0 19 Jan 2017
Conditional Image Generation with PixelCNN Decoders Aaron van den Oord Nal Kalchbrenner Oriol Vinyals L. Espeholt Alex Graves Koray Kavukcuoglu VLM 165 2,503 0 16 Jun 2016
Improving Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma Tim Salimans Rafal Jozefowicz Xi Chen Ilya Sutskever Max Welling BDL DRL 105 1,816 0 15 Jun 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 429 2,566 0 25 Jan 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 612 9,290 0 06 Jun 2015
Deep AutoRegressive Networks Karol Gregor Ivo Danihelka A. Mnih Charles Blundell Daan Wierstra AI4TS BDL 83 282 0 31 Oct 2013