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SOFI Developer Meeting Göttingen 28th March 2015
The document discusses the challenges and strategies for implementing high-speed imaging techniques, specifically SOFI (Super-resolution Optical Fluctuation Imaging), for capturing rapid biological processes. Key issues include integration, timing, memory, and data processing challenges linked to achieving subpixel resolution and real-time imaging of dynamic systems. A roadmap for development emphasizes the importance of efficient hardware and software integration while maintaining user-friendliness.
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SOFI Developer Meeting Göttingen 28th March 2015
- 1. Vistas for hardwareimplementation of SOFI: High speed imaging for rapid biological processes Imaging fast, user-friendly and integrate with ease Dirk Hähnel III. Institute of Physics – Biophysics Georg-August-University Göttingen SOFI Developer Meeting Göttingen 28th March 2015 Göttingen 28th March 2015
- 2. 2 Making it easyand user-friendly? Göttingen 28th March 2015 6. price < 10thd. USD 1. physicist 2. chemicist 3. artifacts 4. image stacks 5. dynamical biosystems CSDISMRequirements Palm Storm SIM SSIM Sted Tirf SOFI
- 3. 3 Why speed isimportant? Göttingen 28th March 2015 atomic scale 0.1 - 1.0 nm dynamic data 0.1 - 10 ns molecular dynamics molecular scale 1.0 - 10 nm interaction data Kon, Koff, Kd 10 ns - 10 ms interactions cellular scale 10 - 100 nm concentrations diffusion rates 10 ms - 1000 s fluid dynamics
- 4. 4 • tier 1:interatome – which molecules talk to each other in networks? • tier 2: deterministic – what is the average case behavior? • tier 3: stochastic – what is the variance of the system? Why integration is important? Göttingen 28th March 2015
- 5. 6 Fast SOFI: crucialchallenges • subpixel resolution • linearize brightness • multiplane imaging Göttingen 28th March 2015 • timing / speed • memory allocation • cumulants computation • integration • scaling physical and experimental challenges: implementation challenges
- 6. 7 Implementation: timing challenge Göttingen28th March 2015 acquisition image reconstruction final SOFI image acquisition image reconstruction Final SOFI Image Imaging today: no dynamics Imaging dynamical biological processes live imaging real time reconstruction 𝑡 𝑎𝑐𝑞𝑢𝑖𝑠𝑖𝑡𝑖𝑜𝑛 ≥ 𝑡 𝑟𝑒𝑐𝑜𝑛𝑠𝑡𝑟𝑢𝑐𝑡𝑖𝑜𝑛
- 7. 8 Implementation: memory challenge Göttingen28th March 2015 subpixel = more gates subpixel = more time cumulants => data swapping linearization => very complex start input frame SCMOS input: 3 Gpixel => SOFI image 1,5 GByte => SOFI image SCMOS subpixel: 12 Gpixel => SOFI image 6 GByte => SOFI image … end
- 8. 9 Implementation: cumulants computationchallenge Göttingen 28th March 2015 challenge: memory space < data 3D stack 𝑛 𝑡ℎ cumulants are 𝑛 𝑡ℎ moments corrected by lower order moments Tremendous matrix operations
- 9. 10 Implementation: integration challenge Göttingen28th March 2015 features: • no intermediate data • open API • micromanager integration
- 10. 11 Implementation: scaling systemarchitecture challenge Göttingen 28th March 2015 hardware schematic software schematic cam n cam n-1 hardware bus cam 0 cam 1 data layer Buffer Reconstruction computation original data intermediate constant cam(s) stream Intermediate data application layer interface
- 11. 12 Integration and developmentroadmap Imaging of dynamical biological systems: acquisition time > image reconstruction Göttingen 28th March 2015 camera link FFT cumulants linearization micromanager integration IIIQ 2015 integration • standard FPGA card • beta software mid 2015 • setup recipe • complexity blackbox
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