arXiv subjects

Iulius Dragonu

Publications and source records attributed to Iulius Dragonu.

4 recordsLinked to original sources

arXiv2026

Rapid online deep artifact suppression for real-time spiral bSSFP CMR with blipped-CAIPI simultaneous multi-slice imaging at 1.5 T

Purpose: Real-time (RT) bSSFP MRI enables fast free-breathing cardiovascular imaging but requires 10-16 slices for functional assessment, resulting in prolonged scan times. Simultaneous multi-slice (SMS) imaging can reduce acquisition time but when combined with non-Cartesian trajectories, it relies on iterative reconstructions that preclude online use. This study investigates deep artifact suppression to facilitate rapid, online reconstruction of RT-SMS. Methods: A spiral bSSFP SMS RT sequence with two simultaneously acquired slices was implemented at 1.5 T. Reconstruction used slice separation in k-space, followed by deep artifact suppression in image space using a 3D U-Net. Ten healthy volunteers were imaged. RT-SMS image quality and reconstruction time were compared between deep artifact suppression and compressed sensing (CS) reconstructions. Left (LV) and right (RV) ventricular volumes at end diastole (EDV) and end systole (ESV) and LV mass (LVM) were compared between RT-SMS with deep artifact suppression and reference-standard breath-hold (BH) imaging. Results: The RT-SMS acquisition was ~13x faster than BH imaging (15 s vs 3 min 15 s). RT-SMS reconstruction using deep artifact suppression was ~50x faster than CS (30 s vs 24 min 55 s). Deep artifact suppression consistently outperformed CS in quantitative and qualitative image quality (p<0.001). Functional agreement between BH and RT-SMS with deep artifact suppression was good (LVEDV: -7.5 +/- 6.8 ml, LVESV: -0.9 +/- 4.2 ml, RVEDV: -6.4 +/- 8.4 ml, RVESV: 0.2 +/- 10.7 ml, LVM: -10.3 +/- 11.0 g). Conclusion: Online deep artifact suppression reconstruction for RT-SMS bSSFP CMR enables free-breathing short-axis coverage with a substantial reduction in acquisition and reconstruction time while maintaining diagnostic image quality.

physics.med-ph↗

arXiv2025

Real-time, inline quantitative MRI enabled by scanner-integrated machine learning: a proof of principle with NODDI

Purpose: The clinical feasibility and translation of many advanced quantitative MRI (qMRI) techniques are inhibited by their restriction to 'research mode', due to resource-intensive, offline parameter estimation. This work aimed to achieve 'clinical mode' qMRI, by real-time, inline parameter estimation with a trained neural network (NN) fully integrated into a vendor's image reconstruction environment, therefore facilitating and encouraging clinical adoption of advanced qMRI techniques. Methods: The Siemens Image Calculation Environment (ICE) pipeline was customised to deploy trained NNs for advanced diffusion MRI parameter estimation with Open Neural Network Exchange (ONNX) Runtime. Two fully-connected NNs were trained offline with data synthesised with the neurite orientation dispersion and density imaging (NODDI) model, using either conventionally estimated (NNMLE) or ground truth (NNGT) parameters as training labels. The strategy was demonstrated online in two healthy volunteers (one rescanned) and evaluated offline with synthetic data, testing two diffusion protocols. Results: NNs were successfully integrated and deployed natively in ICE, performing inline, whole-brain, in vivo NODDI parameter estimation in <10 seconds. The proposed workflow was reproducible across protocols, volunteers and rescans. DICOM parametric maps were exported from the scanner for further analyses. Comparisons between NNMLE and NNGT suggested NNMLE parameter estimates to be more consistent with conventional fitting, a finding supported by offline evaluations. Conclusion: Real-time, inline parameter estimation with the proposed generalisable framework resolves a key practical barrier to the potential clinical uptake of advanced qMRI methods, enabling their efficient integration into clinical workflows. Next steps include incorporation of pre-processing methods and evaluation in pathology.

physics.med-ph↗

arXiv2020

Accelerated calibrationless parallel transmit mapping using joint transmit and receive low-rank tensor completion

Purpose: To evaluate an algorithm for calibrationless parallel imaging to reconstruct undersampled parallel transmit field maps for the body and brain. Methods: Using synthetic data, body, and brain measurements of relative transmit maps, three different approaches to a joint transmit-receive low-rank tensor completion algorithm are evaluated. These methods included: (i) virtual coils using the product of receive and transmit sensitivities, (ii) joint-receiver coils that enforces a low rank structure across receive coils of all transmit modes, and (iii) transmit low rank (TxLR) that uses a low rank structure for both receive and transmit modes simultaneously. The performance of each are investigated for different noise levels and different acceleration rates on an 8-channel parallel transmit 7T system. Results: The virtual coils method broke down with increasing noise levels or acceleration rates greater than two producing RMS error greater than 0.1. The joint receiver coils method worked well up to acceleration factors of four, beyond which the RMS error exceeded 0.1. While TxLR enabled an eight-fold acceleration with most RMS errors remaining below 0.1. Conclusion: This work demonstrates that under-sampling factors of up to eight-fold are feasible for transmit array mapping and can be reconstructed using calibrationless parallel imaging methods.

eess.IV↗

arXiv2014

Magnetic properties of materials for MR engineering, micro-MR and beyond

We present the results of a systematic measurement of the magnetic susceptibility of small material samples in a 9.4 T MRI scanner. We measured many of the most widely used materials in MR engineering and MR micro technology, including various polymers, optical and substrate glasses, resins, glues, photoresists, PCB substrates and some fluids. Based on our data, we identify particularly suitable materials with susceptibilities close to water. For polyurethane resins and elastomers, we also show the MR spectra, as they may be a good substitute for silicone elastomers and good casting resins.

cond-mat.mtrl-sci↗