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Filters: Keyword is magnetic resonance imaging  [Clear All Filters]
2021-02-03
Cecotti, H., Richard, Q., Gravellier, J., Callaghan, M..  2020.  Magnetic Resonance Imaging Visualization in Fully Immersive Virtual Reality. 2020 6th International Conference of the Immersive Learning Research Network (iLRN). :205—209.

The availability of commercial fully immersive virtual reality systems allows the proposal and development of new applications that offer novel ways to visualize and interact with multidimensional neuroimaging data. We propose a system for the visualization and interaction with Magnetic Resonance Imaging (MRI) scans in a fully immersive learning environment in virtual reality. The system extracts the different slices from a DICOM file and presents the slices in a 3D environment where the user can display and rotate the MRI scan, and select the clipping plane in all the possible orientations. The 3D environment includes two parts: 1) a cube that displays the MRI scan in 3D and 2) three panels that include the axial, sagittal, and coronal views, where it is possible to directly access a desired slice. In addition, the environment includes a representation of the brain where it is possible to access and browse directly through the slices with the controller. This application can be used both for educational purposes as an immersive learning tool, and by neuroscience researchers as a more convenient way to browse through an MRI scan to better analyze 3D data.

2020-11-30
Machida, H., Fujiwara, T., Fujimoto, C., Kanamori, Y., Tanaka, J., Takezawa, M..  2019.  Magnetic Domain Structures and Magnetic Properties of Lightly Nd-Doped Sm–Co Magnets With High Squareness and High Heat Resistance. IEEE Transactions on Magnetics. 55:1–4.
The relationship between magnetic domain structures and magnetic properties of Nd-doped Sm(Fe, Cu, Zr, Co)7.5 was investigated. In the preparation process, slow cooling between sintering and solution treatment was employed to promote homogenization of microstructures. The developed magnet achieved a maximum energy product, [BH]m, of 33.8 MGOe and coercivity, Hcb, of 11.2 kOe at 25 °C, respectively. Moreover, B-H line at 150 °C was linear, which means that irreversible demagnetization does not occur even at 150 °C. Temperature coefficients of remanent magnetic flux density, Br, and intrinsic coercivity, Hcj, were 0.035%/K and 0.24%/K, respectively, as usual the conventional Sm-Co magnet. Magnetic domain structures were observed with a Kerr effect microscope with a magnetic field applied from 0 to -20 kOe, and then reverse magnetic domains were generated evenly from grain boundaries. Microstructures referred to as “cell structures” were observed with a scanning transmission electron microscope. Fe and Cu were separated to 2-17 and 1-5 phases, respectively. Moreover, without producing impurity phases, Nd showed the same composition behavior with Sm in a cell structure.
2020-04-24
Yu, Jiangfan, Zhang, Li.  2019.  Reconfigurable Colloidal Microrobotic Swarm for Targeted Delivery. 2019 16th International Conference on Ubiquitous Robots (UR). :615—616.

Untethered microrobots actuated by external magnetic fields have drawn extensive attention recently, due to their potential advantages in real-time tracking and targeted delivery in vivo. To control a swarm of microrobots with external fields, however, is still one of the major challenges in this field. In this work, we present new methods to generate ribbon-like and vortex-like microrobotic swarms using oscillating and rotating magnetic fields, respectively. Paramagnetic nanoparticles with a diameter of 400 nm serve as the agents. These two types of swarms exhibits out-of-equilibrium structure, in which the nanoparticles perform synchronised motions. By tuning the magnetic fields, the swarming patterns can be reversibly transformed. Moreover, by increasing the pitch angle of the applied fields, the swarms are capable of performing navigated locomotion with a controlled velocity. This work sheds light on a better understanding for microrobotic swarm behaviours and paves the way for potential biomedical applications.

2020-02-24
Lisec, Thomas, Bodduluri, Mani Teja, Schulz-Walsemann, Arne-Veit, Blohm, Lars, Pieper, Isa, Gu-Stoppel, Shanshan, Niekiel, Florian, Lofink, Fabian, Wagner, Bernhard.  2019.  Integrated High Power Micro Magnets for MEMS Sensors and Actuators. 2019 20th International Conference on Solid-State Sensors, Actuators and Microsystems Eurosensors XXXIII (TRANSDUCERS EUROSENSORS XXXIII). :1768–1771.
Back-end-of-line compatible integration of NdFeB-based micro magnets onto 8 inch Si substrates is presented. Substrate conditioning procedures to enable further processing in a cleanroom environment are discussed. It is shown that permanent magnetic structures with lateral dimensions between 25μm and 2000μm and a depth up to 500μm can be fabricated reliably and reproducibly with a remanent magnetization of 340mT at a standard deviation as low as 5% over the substrate. To illustrate post-processing capabilities, the fabrication of micro magnet arrangements embedded in silicon frames is described.
Moritz, Pierre, Mathieu, Fabrice, Bourrier, David, Saya, Daisuke, Blon, Thomas, Hasselbach, Klaus, Kramer, Roman, Nicu, Liviu, Lacroix, Lise-Marie, Viau, Guillaume et al..  2019.  Development Of Micro-Magnets For The Electromagnetic Transduction Of MEMS. 2019 20th International Conference on Solid-State Sensors, Actuators and Microsystems Eurosensors XXXIII (TRANSDUCERS EUROSENSORS XXXIII). :1748–1751.
This paper presents a new class of high-performance permanent micro-magnets based on the controlled assembly of cobalt nanorods for the electromagnetic transduction of MEMS. Micromagnets are fabricated using a low temperature fabrication process that yields a dense material exhibiting high coercive field and remanence to saturation magnetization ratio. The cartography of the magnetic induction produced by the sub-millimeter size magnets was obtained using a scanning Hall effect micro-probe microscope. Silicon microcantilevers placed in the vicinity of these magnets were successfully actuated using the Lorentz force with low currents. The good signal to noise ratio measured at resonance demonstrates the potentiality of these nanostructured micro-magnets.
2018-05-16
Maity, T., Roy*, S..  2017.  Manipulation of Magnetic Properties by Tunable Magnetic Dipoles in a Ferromagnetic Thin Film. IEEE Magnetics Letters. 8:1–4.
We demonstrate how a unique nanomodulation within a continuous ferromagnetic film can induce magnetic dipoles at predefined, submicrometer scale locations, which can tune the global magnetic properties of the film due to dipole-dipole interactions. Arrays of tunable magnetic dipoles are generated with in-plane and out-of-plane directions, which can be rotated in-plane within the three-dimensional (3-D) modulated structure of a continuous film. In-plane magnetic dipole rotation enables a methodology to control overall magnetic properties of a ferromagnetic thin film. Formation of magnetic dipoles and their tunability were studied in detail by magnetic force microscopy, high-resolution magnetic measurements, and micromagnetic simulation of a nanomodulated Ni45Fe55 alloy film. A pattern larger than a single magnetic domain would normally form a vortex in the remanent state. However, here the unique 3-D nanostructure prevents vortex formation due to the competition between in-plane and out-of-plane dipole-dipole interaction giving rise to a metastable state. Experimentally, at zero remanence, the magnetization goes through a transformation from a metastable to a stable state, where the dipole-dipole interaction depends on their geometrical arrangement. Thus, the magnetic properties of the continuous film can be varied by the proposed pattern geometry. A detail analytical study of the dipolar energy for the system agrees well with the experimental and simulated results.
2017-02-21
H. Kiragu, G. Kamucha, E. Mwangi.  2015.  "A fast procedure for acquisition and reconstruction of magnetic resonance images using compressive sampling". AFRICON 2015. :1-5.

This paper proposes a fast and robust procedure for sensing and reconstruction of sparse or compressible magnetic resonance images based on the compressive sampling theory. The algorithm starts with incoherent undersampling of the k-space data of the image using a random matrix. The undersampled data is sparsified using Haar transformation. The Haar transform coefficients of the k-space data are then reconstructed using the orthogonal matching Pursuit algorithm. The reconstructed coefficients are inverse transformed into k-space data and then into the image in spatial domain. Finally, a median filter is used to suppress the recovery noise artifacts. Experimental results show that the proposed procedure greatly reduces the image data acquisition time without significantly reducing the image quality. The results also show that the error in the reconstructed image is reduced by median filtering.

S. R. Islam, S. P. Maity, A. K. Ray.  2015.  "On compressed sensing image reconstruction using linear prediction in adaptive filtering". 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI). :2317-2323.

Compressed sensing (CS) or compressive sampling deals with reconstruction of signals from limited observations/ measurements far below the Nyquist rate requirement. This is essential in many practical imaging system as sampling at Nyquist rate may not always be possible due to limited storage facility, slow sampling rate or the measurements are extremely expensive e.g. magnetic resonance imaging (MRI). Mathematically, CS addresses the problem for finding out the root of an unknown distribution comprises of unknown as well as known observations. Robbins-Monro (RM) stochastic approximation, a non-parametric approach, is explored here as a solution to CS reconstruction problem. A distance based linear prediction using the observed measurements is done to obtain the unobserved samples followed by random noise addition to act as residual (prediction error). A spatial domain adaptive Wiener filter is then used to diminish the noise and to reveal the new features from the degraded observations. Extensive simulation results highlight the relative performance gain over the existing work.