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1. Damien Rajon
SCIA 2009
Siemens Corporate Research _ Feb 09 - Aug 09
Final year internship
presentation
Optimization of image reconstruction algorithms

2. Presentation Outline
Company presentation
Internship topic
Technical aspect
Background knowledge
Actual work
Conclusion

3. The company

4. The company
Siemens AG
Founded in 1847 by Werner Von Siemens
One of Europe's largest conglomerate
Over 480 000 employees in 190
countries
Focused on three main sectors
Net income of 4, 038 billion euros

5. The company
Siemens Corporate Research
Founded in 1977
Located in Princeton, New Jersey
Research and development center
Provides technological solutions to other Siemens
businesses
Experts and scientifics from around the world

6. The company
Imaging and Visualization
60 Research scientists
Medical image analysis and visualization solutions
Improve vision and rendering methods of the inside of
the human body
Improve current imaging and analysis techniques

7. The company
Organization hierarchy

8. Internship Topic

9. Internship topic
Context
Locate time consuming parts of the image
reconstruction algorithm
Optimize them
Create a showcase for these optimizations and present
it to the client

10. Internship topic
Organization
Informal and formal
status reports
Meetings with
image
reconstruction
experts

11. Technical aspect

12. Technical aspect
Magnetic Resonance Imaging
Why MRI ?
How does it work ?
k-space vs. image space
Limitations and solutions

13. Technical aspect
GRAPPA
pMRI technique
Reconstruction occurs in k-space
Under-sampling according to a Reduction factor

14. Technical aspect
GRAPPA
Image data
ACS data

15. Technical aspect
GRAPPA
Reduction factor (R) R 1x 2x 3x 4x
relative to SNR SNR 1 0.7 0.5 0.4

16. Technical aspect
GRAPPA - Weights computation

17. Technical aspect
GRAPPA - Weights computation
How to combine all the source data
in order to obtain the target data ?

18. Technical aspect
GRAPPA - Weights computation

19. Technical aspect
GRAPPA - Weights computation
Source data

20. Technical aspect
GRAPPA - Weights computation
Target data

21. Technical aspect
GRAPPA - Weights computation
Weights

22. Technical aspect
GRAPPA - Missing data estimation
Shift the same kernel
in the image data
Use the computed
weights to estimate
missing k-space data

23. Technical aspect
GRAPPA - Image output
All the k-space data is available
Inverse Fourier Tranform
Images from each coil are combined by taking the root
of the Sum Of Squares

24. Technical aspect
GRAPPA - Image output

25. Technical aspect
Image Calculation Environment
Classified as confidential
Framework used within MRI systems
Complex server-client architecture
Image calculation dedicated environment
Reverse engineering

26. Technical aspect
Optimization - Profiling
Log profiling
Source code analysis
Creation of log parsing scripts (AWK, shell script,
python)

27. Technical aspect
Optimization - Weights computation
Cholesky decomposition used to solve the Aw=B
system
8210937600 additions and multiplications to build
matrix A
Reference application uses naive implementation
Use of Intel’s MKL

28. Technical aspect
Optimization - Weights computation
3 implementations
to meet different
needs
Huge performance
gain

29. Technical aspect
Optimization - Weights computation

30. Technical aspect
Showcase
Build a standalone application
Further optimizations

31. Conclusion

32. Conclusion
Work on bleeding edge pMRI techniques
Work on an actual product
Knowledge in medical imaging
Difficulties
Reverse engineering a massive project
Lack of medical imaging knowledge

33. Conclusion
Professional outcome
Improved medical imaging knowledge
Real scale project
Understand and understood
Personal outcome
Improvement in English
Work in the USA
Work in a renown company
Meet interesting people from around the world

34. Thank you for listening
Any questions ?