Design of a high-torque machine with two integrated motors axes reducing the electric vehicle consumption

The motorization of electric vehicle needs to work at a constant power on a wide range of speed. In order to be able to satisfy these requirements, we describe in this paper a solution, which consists in modifying of a simple structure of a permanent magnet motor by a double rotor structure integrating two motor axes into the same machine. This article describes, then, a design methodology of a permanent magnet motor with double rotor, radial flux, and strong starting torque for electric vehicles. This work consists on the analytical dimensioning of the motor by taking into account several operation constraints followed by a modelling by the finite elements method. This study is followed by the comparison between this motor and a motor with one rotor. A global model of the motor- converter is developed for the purpose to answer several optimisation problem

A Comparative Study of Permanent Magnet Motor Cost Minimization Dedicated to Electric Traction JES Journal of Electrical Systems

In this paper, we present a permanent magnet motor cost minimization dedicated to the electric traction based on a genetic algorithms (GAs) method. Our objective is to minimize this cost by taking account of certain constraints. The choice of a suitable coding is a critical element which depends largely on the genetic algorithm effectiveness. That is why we present a comparative study between two types of genetic algorithms i.e. a binary coded genetic algorithm (BCGA) and a real coded genetic algorithm (RCGA)

CINENet: deep learning-based 3D cardiac CINE MRI reconstruction with multi-coil complex-valued 4D spatio-temporal convolutions

Cardiac CINE magnetic resonance imaging is the gold-standard for the assessment of cardiac function. Imaging accelerations have shown to enable 3D CINE with left ventricular (LV) coverage in a single breath-hold. However, 3D imaging remains limited to anisotropic resolution and long reconstruction times. Recently deep learning has shown promising results for computationally efficient reconstructions of highly accelerated 2D CINE imaging. In this work, we propose a novel 4D (3D + time) deep learning-based reconstruction network, termed 4D CINENet, for prospectively undersampled 3D Cartesian CINE imaging. CINENet is based on (3 + 1)D complex-valued spatio-temporal convolutions and multi-coil data processing. We trained and evaluated the proposed CINENet on in-house acquired 3D CINE data of 20 healthy subjects and 15 patients with suspected cardiovascular disease. The proposed CINENet network outperforms iterative reconstructions in visual image quality and contrast (+ 67% improvement). We found good agreement in LV function (bias ± 95% confidence) in terms of end-systolic volume (0 ± 3.3 ml), end-diastolic volume (- 0.4 ± 2.0 ml) and ejection fraction (0.1 ± 3.2%) compared to clinical gold-standard 2D CINE, enabling single breath-hold isotropic 3D CINE in less than 10 s scan and ~ 5 s reconstruction time

PET/MRI attenuation estimation in the lung: A review of past, present, and potential techniques

Positron emission tomography/magnetic resonance imaging (PET/MRI) potentially offers several advantages over positron emission tomography/computed tomography (PET/CT), for example, no CT radiation dose and soft tissue images from MR acquired at the same time as the PET. However, obtaining accurate linear attenuation correction (LAC) factors for the lung remains difficult in PET/MRI. LACs depend on electron density and in the lung, these vary significantly both within an individual and from person to person. Current commercial practice is to use a single-valued population-based lung LAC, and better estimation is needed to improve quantification. Given the under-appreciation of lung attenuation estimation as an issue, the inaccuracy of PET quantification due to the use of single-valued lung LACs, the unique challenges of lung estimation, and the emerging status of PET/MRI scanners in lung disease, a review is timely. This paper highlights past and present methods, categorizing them into segmentation, atlas/mapping, and emission-based schemes. Potential strategies for future developments are also presented

Motion estimation and correction for simultaneous PET/MR using SIRF and CIL

SIRF is a powerful PET/MR image reconstruction research tool for processing data and developing new algorithms. In this research, new developments to SIRF are presented, with focus on motion estimation and correction. SIRF's recent inclusion of the adjoint of the resampling operator allows gradient propagation through resampling, enabling the MCIR technique. Another enhancement enabled registering and resampling of complex images, suitable for MRI. Furthermore, SIRF's integration with the optimization library CIL enables the use of novel algorithms. Finally, SPM is now supported, in addition to NiftyReg, for registration. Results of MR and PET MCIR reconstructions are presented, using FISTA and PDHG, respectively. These demonstrate the advantages of incorporating motion correction and variational and structural priors. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'

Simultaneous 13N-Ammonia and gadolinium first-pass myocardial perfusion with quantitative hybrid PET-MR imaging: a phantom and clinical feasibility study

Background Positron emission tomography (PET) is the non-invasive reference standard for myocardial blood flow (MBF) quantification. Hybrid PET-MR allows simultaneous PET and cardiac magnetic resonance (CMR) acquisition under identical experimental and physiological conditions. This study aimed to determine feasibility of simultaneous 13N-Ammonia PET and dynamic contrast-enhanced CMR MBF quantification in phantoms and healthy volunteers. Methods Images were acquired using a 3T hybrid PET-MR scanner. Phantom study: MBF was simulated at different physiological perfusion rates and a protocol for simultaneous PET-MR perfusion imaging was developed. Volunteer study: five healthy volunteers underwent adenosine stress. 13N-Ammonia and gadolinium were administered simultaneously. PET list mode data was reconstructed using ordered subset expectation maximisation. CMR MBF was quantified using Fermi function-constrained deconvolution of arterial input function and myocardial signal. PET MBF was obtained using a one-tissue compartment model and image-derived input function. Results Phantom study: PET and CMR MBF measurements demonstrated high repeatability with intraclass coefficients 0.98 and 0.99, respectively. There was high correlation between PET and CMR MBF (r = 0.98, p < 0.001) and good agreement (bias − 0.85 mL/g/min; 95% limits of agreement 0.29 to − 1.98). Volunteer study: Mean global stress MBF for CMR and PET were 2.58 ± 0.11 and 2.60 ± 0.47 mL/g/min respectively. On a per territory basis, there was moderate correlation (r = 0.63, p = 0.03) and agreement (bias − 0.34 mL/g/min; 95% limits of agreement 0.49 to − 1.18). Conclusion Simultaneous MBF quantification using hybrid PET-MR imaging is feasible with high test repeatability and good to moderate agreement between PET and CMR. Future studies in coronary artery disease patients may allow cross-validation of techniques

Motion estimation and correction for simultaneous PET/MR using SIRF and CIL

SIRF is a powerful PET/MR image reconstruction research tool for processing data and developing new algorithms. In this research, new developments to SIRF are presented, with focus on motion estimation and correction. SIRF's recent inclusion of the adjoint of the resampling operator allows gradient propagation through resampling, enabling the MCIR technique. Another enhancement enabled registering and resampling of complex images, suitable for MRI. Furthermore, SIRF's integration with the optimization library CIL enables the use of novel algorithms. Finally, SPM is now supported, in addition to NiftyReg, for registration. Results of MR and PET MCIR reconstructions are presented, using FISTA and PDHG, respectively. These demonstrate the advantages of incorporating motion correction and variational and structural priors. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'

Late Gadolinium Enhancement Cardiovascular Magnetic Resonance Assessment of Substrate for Ventricular Tachycardia With Hemodynamic Compromise.

Background: The majority of data regarding tissue substrate for post myocardial infarction (MI) VT has been collected during hemodynamically tolerated VT, which may be distinct from the substrate responsible for VT with hemodynamic compromise (VT-HC). This study aimed to characterize tissue at diastolic locations of VT-HC in a porcine model. Methods: Late Gadolinium Enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging was performed in eight pigs with healed antero-septal infarcts. Seven pigs underwent electrophysiology study with venous arterial-extra corporeal membrane oxygenation (VA-ECMO) support. Tissue thickness, scar and heterogeneous tissue (HT) transmurality were calculated at the location of the diastolic electrograms of mapped VT-HC. Results: Diastolic locations had median scar transmurality of 33.1% and a median HT transmurality 7.6%. Diastolic activation was found within areas of non-transmural scar in 80.1% of cases. Tissue activated during the diastolic component of VT circuits was thinner than healthy tissue (median thickness: 5.5 mm vs. 8.2 mm healthy tissue, p < 0.0001) and closer to HT (median distance diastolic tissue: 2.8 mm vs. 11.4 mm healthy tissue, p < 0.0001). Non-scarred regions with diastolic activation were closer to steep gradients in thickness than non-scarred locations with normal EGMs (diastolic locations distance = 1.19 mm vs. 9.67 mm for non-diastolic locations, p < 0.0001). Sites activated late in diastole were closest to steep gradients in tissue thickness. Conclusions: Non-transmural scar, mildly decreased tissue thickness, and steep gradients in tissue thickness represent the structural characteristics of the diastolic component of reentrant circuits in VT-HC in this porcine model and could form the basis for imaging criteria to define ablation targets in future trials