1. Imaging Science Department, IC Jo Hajnal (jo.hajnal@ic.ac.uk)
Development and exploitation of medical & biological Imaging
About 30 research staff
Main Groups
Imaging Physics and Engineering
In vivo MRI
In vivo Ultrasound
Biological Imaging Centre
IPEL research
Physics and Engineering of imaging
Technology for MRI and US (RF fields in MHz range)
Data acquisition
Image reconstruction and data processing
Informatics for medical imaging

2. Magnetic Resonance Scanners
Superconducting cryomagnets

3. MRI scans: can choose location, imaging plane and contrast between tissues
T1weighted
T2 weighted
Pd weighted

4. NMR process
Signal from spin 1/2 nuclei- MRI exploits hydrogen nucleus in mobile water molecules and fat
RF Transmitter
RF Receiver
Sample N S
Polarizing Magnet
NMR Signal
Intensity
Frequency
NMR Spectrum
Fourier
Transformation
FID
(Free Induction Decay)

5. Fourier Transformation
Image formation requires spatial encoding
Gradients in B0 make Larmor Frequency linearly dependent on spatial position
In the presence of the gradient both samples sense different fields... Z Y X
Intensity
Fourier Transformation
Frequency
Time
…samples differentiated.

6. Gradient Coils
X Coils
Y Coils
Z Coils

7. More formally……… Signal from object is (x,y)
Acquired signal with spatial encoding is S(kx,ky)
where
Image space
k-space

8. MRI data acquired in Fourier domainFT

9. For optimal sensitivity- match receive coil to task
36cm FoV
25cm FoV
10cm FoV
Body coil
Head coil
Internal coil

10. Diffusion Tensor imaging
Angiography
Diffusion Tensor imaging
Martyn Paley, Sheffield
Fat suppression

11. Magnetic fields in MRI and Magnetic materials
Field Strength Frequency
Static polarising field: B T 0Hz
Gradient fields: G 10 –200mT/m Hz
RF fields B1 25T MHz
In general require B0and B1 to be homogeneous, G to be linear
Hitherto, have not had any magnetic materials to manipulate B1, without making B0 unusable
Requirements on B0 typically < 3ppm

12. RF fields and spatial encoding
Previously…..
Now include spatial variation of RF receive sensitivity
Conventionally, we regard Cj as simply modifying the object, but it can be used for spatial encoding

13. ISD contribution and collaboration
Imaging Science team
Mike Wiltshire- Physicist
David Larkman- Physicist
Ian Young - Physicist/Engineer
David Gilderdale- RF Engineer
MRI application- key issues
Near field shaping
Noise/loss
Encoding/Image transfer
Opportunities
Medical applications
Probing RF fields
Expertise in existing RF technology
Needs
Modelling of MM
Collaboration on fabrication