sofi developer meetinggöttingen 28th march 2015
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Vistas for hardware implementation of SOFI: High speed imaging for rapid biological processes
Imaging fast, user-friendly and integrate with ease
Dirk HähnelIII. Institute of Physics – BiophysicsGeorg-August-University Göttingen
SOFI Developer MeetingGöttingen 28th March 2015
Göttingen 28th March 2015
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Making it easy and 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
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Why speed is important?
Göttingen 28th March 2015
atomic scale0.1 - 1.0 nm
dynamic data0.1 - 10 ns
molecular dynamics
molecular scale1.0 - 10 nm
interaction dataKon, Koff, Kd
10 ns - 10 msinteractions
cellular scale10 - 100 nm
concentrationsdiffusion rates
10 ms - 1000 sfluid dynamics
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• 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
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Fast SOFI: crucial challenges
• subpixel resolution
• linearize brightness
• multiplane imaging
Göttingen 28th March 2015
• timing / speed
• memory allocation
• cumulants computation
• integration
• scaling
physical and experimental challenges: implementation challenges
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Implementation: timing challenge
Göttingen 28th March 2015
acquisition
image reconstruction
final SOFI image
acquisition image reconstruction
Final SOFI Image
Imaging today: no dynamics Imaging dynamical biological processes
live imagingreal time reconstruction
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Implementation: memory challenge
Göttingen 28th March 2015
subpixel = more gates subpixel = more timecumulants => data swappinglinearization => very complex
start
input frame
SCMOS input:3 Gpixel => SOFI image1,5 GByte => SOFI image
SCMOS subpixel:12 Gpixel => SOFI image6 GByte => SOFI image
…
end
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Implementation: cumulants computation challenge
Göttingen 28th March 2015
challenge:memory space < data 3D stack
cumulants are moments corrected by lower order moments
Tremendous matrix operations
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Implementation: integration challenge
Göttingen 28th March 2015
features:• no intermediate data• open API• micromanager integration
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Implementation: scaling system architecture challenge
Göttingen 28th March 2015
hardware schematic software schematic
cam n
cam n-1
hardware bus
cam 0
cam 1
data layer
Buffer
Reconstructioncomputation
originaldataintermediate
constant cam(s)stream
Intermediate
data
application layer interface
scali
ng
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Integration and development roadmap
Imaging of dynamical biological systems:acquisition time > image reconstruction
Göttingen 28th March 2015
camera link
FFTcumulants
linearizationmicromanagerintegration
IIIQ 2015
integration• standard FPGA card • beta software mid 2015• setup recipe• complexity blackbox
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Acknowledgements
Göttingen 28th March 2015
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