activity
20182023
most citedi-RIM applied to the fastMRI challenge

13 citations · 17 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV20211 cited

Subpixel object segmentation using wavelets and multi resolution analysis

Ray Sheombarsing, Nikita Moriakov, Jan-Jakob Sonke +1

We propose a novel deep learning framework for fast prediction of boundaries of two-dimensional simply connected domains using wavelets and Multi Resolution Analysis (MRA). The bou…

eess.IV2020

Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction

Matthew J. Muckley, Bruno Riemenschneider, Alireza Radmanesh +20

Accelerating MRI scans is one of the principal outstanding problems in the MRI research community. Towards this goal, we hosted the second fastMRI competition targeted towards reco…

cs.LG20202 cited

Kernel of CycleGAN as a Principle homogeneous space

Nikita Moriakov, Jonas Adler, Jonas Teuwen

Unpaired image-to-image translation has attracted significant interest due to the invention of CycleGAN, a method which utilizes a combination of adversarial and cycle consistency…

eess.IV201913 cited

i-RIM applied to the fastMRI challenge

Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen +4

We, team AImsterdam, summarize our submission to the fastMRI challenge (Zbontar et al., 2018). Our approach builds on recent advances in invertible learning to infer models as pres…

eess.IV2019

Learned SIRT for Cone Beam Computed Tomography Reconstruction

Roeland J. Dilz, Lukas Schröder, Nikita Moriakov +2

We introduce the learned simultaneous iterative reconstruction technique (SIRT) for tomographic reconstruction. The learned SIRT algorithm is a deep learning based reconstruction m…

physics.optics2018

On Maximum Focused Electric Energy in Bounded Regions

Jonas Teuwen, Paul Urbach

A general method is presented for determining the maximum electric energy in a bounded region of optical fields with given time-averaged flux of electromagnetic energy. Time-harmon…