221 citations · 424 across the 19 of their papers we have counts for
19 papers
Agentic Autoresearch for CT Reconstruction
Andreas Maier, Lucas Kachelriess, Siming Bayer +4
Comparing CT reconstruction methods fairly is labor-intensive and largely manual, and many benchmarks use idealized data. We ask whether a large language model (LLM) agent can do t…
MR Simulation with Phase Distribution Graphs: Off-Resonant Pulse Response and Slice-Selection
Felix Dietz, Jonathan Endres, Simon Weinmueller +2
Purpose: Phase Distribution Graphs were introduced as a powerful tool for on-resonant MRI simulations. Herein, we extend the concept beyond the assumptions of hard and on-resonant…
SIREM: Speech-Informed MRI Reconstruction with Learned Sampling
Md Hasan, Nyvenn Castro, Daiqi Liu +6
Real-time magnetic resonance imaging (rtMRI) of speech production enables non-invasive visualization of dynamic vocal-tract motion and is valuable for speech science and clinical a…
MR-zero meets FLASH -- Controlling the transient signal decay in gradient- and rf-spoiled gradient echo sequences
Simon Weinmüller, Jonathan Endres, Nam Dang +2
Abstract Purpose The complex signal decay during the transient FLASH MRI readout can lead to artifacts in magnitude and phase images. We show that target-driven optimization of ind…
Enhanced and Robust Contrast in CEST MRI: Saturation Pulse Shape Design via Optimal Control
Clemens Stilianu, Christina Graf, Markus Huemer +5
Purpose: To employ optimal control for the numerical design of CEST saturation pulses to maximize contrast and stability against inhomogeneities. Theory and Methods: We appli…
BMapEst: Estimation of Brain Tissue Probability Maps using a Differentiable MRI Simulator
Utkarsh Gupta, Emmanouil Nikolakakis, Moritz Zaiss +1
Reconstructing digital brain phantoms in the form of voxel-based, multi-channeled tissue probability maps for individual subjects is essential for capturing brain anatomical variab…
MR sequence design to account for non-ideal gradient performance
Daniel J West, Felix Glang, Jonathan Endres +4
MRI systems are traditionally engineered to produce close to idealized performance, enabling a simplified pulse sequence design philosophy. An example of this is control of eddy cu…
Image space formalism of convolutional neural networks for k-space interpolation
Peter Dawood, Felix Breuer, Istvan Homolya +4
Purpose: Noise resilience in image reconstructions by scan-specific robust artificial neural networks for k-space interpolation (RAKI) is linked to nonlinear activations in k-space…
Joint MR sequence optimization beats pure neural network approaches for spin-echo MRI super-resolution
Hoai Nam Dang, Vladimir Golkov, Thomas Wimmer +3
Current MRI super-resolution (SR) methods only use existing contrasts acquired from typical clinical sequences as input for the neural network (NN). In turbo spin echo sequences (T…
Scale-Equivariant Deep Learning for 3D Data
Thomas Wimmer, Vladimir Golkov, Hoai Nam Dang +3
The ability of convolutional neural networks (CNNs) to recognize objects regardless of their position in the image is due to the translation-equivariance of the convolutional opera…
Accelerated and Quantitative 3D Semisolid MT/CEST Imaging using a Generative Adversarial Network (GAN-CEST)
Jonah Weigand-Whittier, Maria Sedykh, Kai Herz +7
Purpose: To substantially shorten the acquisition time required for quantitative 3D chemical exchange saturation transfer (CEST) and semisolid magnetization transfer (MT) imaging a…
snapshot CEST++ : the next snapshot CEST for fast whole-brain APTw imaging at 3T
Patrick Liebig, Maria Sedykh, Kai Herz +6
CEST suffers from two main problems long acquisitin times or restricted coverage as well as incoherent protocol settings. In this paper we give suggestions on how to optimise your…
Towards Super-Resolution CEST MRI for Visualization of Small Structures
Lukas Folle, Katharian Tkotz, Fasil Gadjimuradov +9
The onset of rheumatic diseases such as rheumatoid arthritis is typically subclinical, which results in challenging early detection of the disease. However, characteristic changes…
An End-to-End AI-Based Framework for Automated Discovery of CEST/MT MR Fingerprinting Acquisition Protocols and Quantitative Deep Reconstruction (AutoCEST)
Or Perlman, Bo Zhu, Moritz Zaiss +2
Purpose: To develop an automated machine-learning-based method for the discovery of rapid and quantitative chemical exchange saturation transfer (CEST) MR fingerprinting acquisitio…
MRzero -- Fully automated discovery of MRI sequences using supervised learning
Alexander Loktyushin, Kai Herz, Nam Dang +7
Purpose: A supervised learning framework is proposed to automatically generate MR sequences and corresponding reconstruction based on the target contrast of interest. Combined with…
CEST MR-Fingerprinting: practical considerations and insights for acquisition schedule design and improved reconstruction
Or Perlman, Kai Herz, Moritz Zaiss +3
Purpose: To understand the influence of various acquisition parameters on the ability of CEST MR-Fingerprinting (MRF) to discriminate different chemical exchange parameters and to…
DeepCEST: 9.4 T Chemical Exchange Saturation Transfer MRI contrast predicted from 3 T data - a proof of concept study
Moritz Zaiss, Anagha Deshmane, Mark Schuppert +6
Purpose: Separation of different CEST signals in the Z-spectrum is a challenge especially at low field strengths where amide, amine, and NOE peaks coalesce with each other or with…
Inverse Z-spectrum analysis for MT- and spillover-corrected and T1-compensated steady-state pulsed CEST-MRI - application to pH-weighted MRI of acute stroke
Moritz Zaiss, Junzhong Xu, Steffen Goerke +5
Endogenous chemical exchange saturation transfer (CEST) effects are always diluted by competing effects such as direct water proton saturation (spillover) and macromolecular magnet…
Exchange-dependent relaxation in the rotating frame for slow and intermediate exchange - modeling off-resonant spin-lock and chemical exchange saturation transfer
Moritz Zaiss, Peter Bachert
Chemical exchange observed by NMR saturation transfer (CEST) and spin-lock (SL) experiments provide an MRI contrast by indirect detection of exchanging protons. The determination o…