MRI

META COIL, Новый физтех
МРТ, Новый физтех

Nowadays magnetic resonance imaging (MRI) is a cut-edge medical imaging technology with its high information content and the accuracy of the data acquisition. It provides a non-invasive and a relatively safe method of examining patients.

We are working with breakthrough ideas and developing unique skills to extend the MRI capabilities.

We are currently collaborating with specialists in various fields such as radio-physicists and those who specialize in the physics of magnetic resonance, radiologists and clinical specialists, mathematicians, programmers and engineers.

In particular, we are collaborating with clinical specialists on the projects that are dedicated to the use of special devices made with the use of new materials and neural network algorithms. These devices are specifically designed for cancer screening, heart function assessment and the diagnosis of complex joints arthritis. We are working on predicting the development of scoliosis as well as on the functional studies of the human brain, the examination of the peripheral nervous system and the energy processes in muscle tissues.

We are now developing new methods for the image reconstruction and the data collection aiming at making MRI scans faster, safer and more accurate.

Our physicists are searching for the ways to turn matematerials, metasurfaces and special ceramics into new and more efficient receiving and transmitting antennas for MRI. They are studying ultra-high-Q, ultra-wideband, time-varying and almost invisible devices in terms of their application and the possibility of extending the capabilities of tomography.

Our engineers are creating devices for ultrafast scanning, simultaneous scanning of various atoms for focusing MRI on individual anatomical areas or organs, for suppressing electrical and acoustic noise and for completely wireless data transmission in MRI.

We make MRI better.

Staff

META COIL, Новый физтех
МРТ, Новый физтех

Publications

2020

2019

21.
Control of the magnetic near-field pattern inside MRI-machine with tunable metasurface
[DOI:
10.1063/1.5099413
] [ IF:
3.521
, SJR:
1.331
]
20.
Marine A. C. Moussu
Luisa Ciobanu
Sergej Kurdjumov
Elizaveta Nenasheva
Boucif Djemai
Marc Dubois
Andrew G. Webb
Stefan Enoch
Redha Abdeddaim
  , vol.
31
, pp.
1900912
, 2019
[DOI:
10.1002/adma.201900912
] [ IF:
25.809
, SJR:
10.108
]
19.
Masoud Sharifian Mazraeh Mollaei
Sergei Kurdjumov
, vol.
164
, pp.
155-166
, 2019
[DOI:
10.2528/pier18101703
] [ IF:
2.322
]
18.
de Muinck Keizer Daan M.
Pathmanathan Angela U.
Kerkmeijer Linda G.W.
van der Voort van Zyp Jochem RN
Tree Alison C
C.A.T. van den Berg
JCJ de_Boer
, vol.
64
, pp.
07NT02
, 2019
[DOI:
10.1088/1361-6560/ab09a6
] [ IF:
3.030
, SJR:
1.297
]

2018

15.
13.
M.S.M. Mollaei
Sergei Kurdjumov
[DOI:
10.1016/j.photonics.2018.10.001
] [ IF:
1.575
, SJR:
0.433
]
11.
Mikhail Gulyaev V.
Nikolai Anisimov V.
Dmitry Volkov V.
Yury Pirogov A.
, vol.
31(8)
, pp.
e3952
, 2018
[DOI:
10.1002/nbm.3952
] [ IF:
3.031
, SJR:
1.451
]
10.
, vol.
291
, pp.
47-52
, 2018
[DOI:
https://doi.org/10.1016/j.jmr.2018.04.010
] [ IF:
2.586
, SJR:
1.182
]
9.
van den Berg Cornelis A.T.
Dmitriev Dmitry S.
Aleksandr Efimtcev Y.
Andrey Sokolov V.
Fokin Vladimir A.
, vol.
80
, pp.
1726-1737
, 2018
[DOI:
10.1002/mrm.27140
] [ IF:
4.082
, SJR:
1.890
]
7.
Anton Nikulin
Elodie Georget
Benoit Larrat
Djamel Berrahou
Luisa Neves
Pierre Sabouroux
Stefan Enoch
Redha Abdeddaim
, vol.
8
, pp.
9190
, 2018
[DOI:
10.1038/s41598-018-27327-y
] [ IF:
4.122
, SJR:
1.533
]

2017

6.
, vol.
112
, pp.
33501
, 2017
[DOI:
10.1063/1.5013319
] [ IF:
3.411
, SJR:
1.673
]
4.
Paul de_Bruin
Irena Zivkovic
Efthymios Kallos
Andrew Webb
, vol.
286
, pp.
78-81
, 2017
[DOI:
10.1016/j.jmr.2017.11.013
] [ IF:
2.432
, SJR:
1.016
]

2016

2.
  , vol.
28
, pp.
1832-1838
, 2016
[DOI:
10.1002/adma.201504270
] [ IF:
18.960
, SJR:
8.625
]

2014