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Found 10 papers, 6 papers with code
Equilibrium Model with Anisotropy for Model-Based Reconstruction in Magnetic Particle Imaging
Magnetic particle imaging is a tracer-based tomographic imaging technique that allows the concentration of magnetic nanoparticles to be determined with high spatio-temporal resolution.
Resonant Inductive Coupling Network for Human-Sized Magnetic Particle Imaging
In addition, the decoupling of multiple drive field channels is discussed and the primary side of the transformer is evaluated for maximum coupling and minimum stray field.
MRIReco.jl: An MRI Reconstruction Framework written in Julia
Methods: Julia is a modern, general purpose programming language with strong features in the area of signal / image processing and numerical computing.
MRI Reconstruction
Medical Physics
Programming Languages
A simulation framework for particle magnetization dynamics of large ensembles of single domain particles: Numerical treatment of Brown/Néel dynamics and parameter identification problems in magnetic particle imaging
Magnetic nanoparticles and their magnetization dynamics play an important role in many applications.
Efficient Joint Estimation of Tracer Distribution and Background Signals in Magnetic Particle Imaging using a Dictionary Approach
Background signals are a primary source of artifacts in magnetic particle imaging and limit the sensitivity of the method since background signals are often not precisely known and vary over time.
Smart Chest X-ray Worklist Prioritization using Artificial Intelligence: A Clinical Workflow Simulation
Our simulations demonstrate that smart worklist prioritization by AI can reduce the average RTAT for critical findings in CXRs while maintaining a small maximum RTAT as FIFO.
3d-SMRnet: Achieving a new quality of MPI system matrix recovery by deep learning
In this work, we propose a novel framework with a 3d-System Matrix Recovery Network and demonstrate it to recover a 3d system matrix with a subsampling factor of 64 in less than one minute and to outperform CS in terms of system matrix quality, reconstructed image quality, and processing time.
When does Bone Suppression and Lung Field Segmentation Improve Chest X-Ray Disease Classification?
Chest radiography is the most common clinical examination type.
Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification
The increased availability of X-ray image archives (e. g. the ChestX-ray14 dataset from the NIH Clinical Center) has triggered a growing interest in deep learning techniques.
MDF: Magnetic Particle Imaging Data Format
The aim of the Magnetic Particle Imaging Data Format (MDF) is to provide a coherent way of exchanging MPI and MPS data acquired with different devices worldwide.
Medical Physics
