Near Real-Time Deconvolution for 3D Fluorescence Microscopy Marc - - PowerPoint PPT Presentation

near real time deconvolution for 3d fluorescence
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Near Real-Time Deconvolution for 3D Fluorescence Microscopy Marc - - PowerPoint PPT Presentation

Near Real-Time Deconvolution for 3D Fluorescence Microscopy Marc Bruce, PhD CEO, Microvolution GPU Accelerated Deconvolution Software After 3-D Deconvolution Other Deconvolution 16 Seconds 10.7 Min Thin Filaments Are Missing Preserves Thin


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SLIDE 1

Near Real-Time Deconvolution for 3D Fluorescence Microscopy

Marc Bruce, PhD CEO, Microvolution

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SLIDE 2

GPU Accelerated Deconvolution Software

Microvolution offers faster and more accurate deconvolution

Thin Filaments Are Missing Preserves Thin Filaments: 16 sec

Image Courtesy of Molecular Devices

Other Deconvolution 10.7 Min After 3-D Deconvolution 16 Seconds

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SLIDE 3

Basics of f Fluorescence Microscopy

Sample Objective

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SLIDE 4

Basics of f Fluorescence Microscopy

Illumination Dichroic mirror

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SLIDE 5

Basics of f Fluorescence Microscopy

Emission

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SLIDE 6

Basics of f Fluorescence Microscopy

  • Damage to sample from high

intensity light

  • Haze from out-of-plane

fluorescence

  • Blurriness due to diffraction

reduces resolution of small

  • bjects

Derived from Wikipedia, “Light sheet fluorescence microscopy”

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SLIDE 7

Diffraction Limits 3D Resolution

XY Z X Y

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SLIDE 8

Point Spread Function

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SLIDE 9

The Solution: Deconvolution Software

http://www.leica-microsystems.com/science-lab/deconvolution

XY Z

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SLIDE 10

Richardson Lucy Algorithm

Iterative algorithm operating under the assumptions of Poisson- distributed noise

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SLIDE 11

Real-time Deconvolution is Now Possible

  • GPU yields speeds up to 200X

faster than old methods

  • Allows for real-time

deconvolution

  • Optimize image capture

145 215 571 900 0.42 1.5 4.8 7.6

100 200 300 400 500 600 700 800 900 1000

10 MB 253x210x50 190 MB 1080x1080x50 890 MB 2160x2160x50 1246 MB 2160x2160x70

Seconds

Old methods GPU accelerated

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SLIDE 12

Higher Signal-to to-Noise Ratio Yields Better Data

  • Analysis of raw FRET images

showed low contrast

  • 4x effective increase in contrast

post-deconvolution

  • Expected cell features can now be

seen

Miskolci, V., Hodgson, L. & Cox, D. Using Fluorescence Resonance Energy Transfer-Based Biosensors to Probe Rho GTPase Activation During Phagocytosis. Methods in Molecular Biology 1519, 125-43 (2017)

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SLIDE 13

Diffraction-Limited Resolution Limit

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SLIDE 14

In Increased Resolution to 180 nm

20 40 60 80 100 120 140 160 180 0.5 1 1.5 2 2.5 3 20 40 60 80 100 120 140 0.5 1 1.5 2 2.5 3

Tong Zhang and Puifai Santisakultarm, Salk Institute

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SLIDE 15

Microscopy in Dim Light

Be Before 2048 x x 2048 x x 51 Aft fter 3D D De Deconvolution 8.5 .5 sec econds

Image Courtesy of Technical Instruments

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SLIDE 16

Widefield Microscopy

Dennis Hughes, MD, PhD, Assoc Prof of Pediatrics, Jared Mortus, Lead Researcher, Laurence Cooper, MD, PhD, Professor of Pediatrics, George McNamara, PhD, Senior Research Scientist, The Children’s Cancer Hospital, MD Anderson Cancer Center, Houston, TX

Wid idefie ield Im Image Be Before 1024 x x 1024 x x 34 Aft fter 3D D De Deconvolution 1.6 .6 sec econds

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SLIDE 17

Light Sheet Microscopy

Derived from Wikipedia, “Light sheet fluorescence microscopy”

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SLIDE 18

Light Sheet Microscopy

Ligh Light Shee eet Im Image Be Before 946 x x 768 x x 321 Aft fter 3D D De Deconvolution 22.5 .5 sec econds

Dong-Yuan Chen in the Bilder lab, UC Berkeley

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SLIDE 19

Lattice Light Sheet Microscopy

  • Dr. Boyd Butler using 3i Lattice LightSheet

LLS LLSM Be Before 1167 x x 512 x x 401 Aft fter 3D D De Deconvolution 10.2 .2 sec econds

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SLIDE 20

In Instant SIM IM

VisiTech

In Instant SIM IM Im Image Be Before 1446 x x 1131 x x 14 Aft fter 3D D De Deconvolution 4.9 .9 sec econds

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SLIDE 21

FINCH (Fresnel in

incoherent corr rrelation holography)

Siegel, N., Lupashin, V., Storrie, B. & Brooker, G. High-magnification super-resolution FINCH microscopy using birefringent crystal lens interferometers. Nature Photonics 10, 802-808 (2016)

Aft fter Propagation and 3D D De Deconvolu lution 10 sec econ

  • nds

Wid idefie ield Im Image 2048 x x 2048 x x 21

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SLIDE 22

Usable on All Tiers of f GPUs

  • HPC clusters
  • Split large multi-channel, multi-timepoint images onto independent nodes
  • Let peer GPUs collaborate
  • Desktops
  • Run alongside acquisition
  • Embedded systems
  • Currently developing for TX1
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SLIDE 23

Usable on All Tiers of f GPUs

5 10 15 20 25 30 35 Seconds

TX1 K2200 970M K40 P5000 GP100

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SLIDE 24

Questions?

Marc Bruce marc@microvolution.com