Image acquisition. Autumn 2007 Mikko Liljeström

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1 Image acquisition Autumn 2007 Mikko Liljeström

2 Microscope Objective (Magnification, NA ) Light source Filters Image acquired can not be better than image generated by microscope (but it can be worse )

3 Imaging device Film camera Digital camera Photomultiplier Tube (PMT)

4 CCD photon detector Thin silicon wafer Divided into array of light sensitive regions (Pixels) Capture image information in the form of a localized electrical charge Charge varies with incident light intensity

5

6 Charges to images Charge per pixel shifted row by row across the register Transferred in sequence from edge of parallel register to serial shift register Charge contents of pixels read and converted to a digital value according to the voltage amplitude Serial readout process is repeated until all pixel rows of the parallel register are emptied CCD is cleared of residual charge prior to next exposure

7 Chip Architecture CCD Directly from imaging area to shift register Frame transfer CCD Link 2 part sensor, via storage region Interline transfer CCD 2 part sensor, via charge transfer channels

8 CCD Format Large range of sensor sizes 2/3 inch (actually 8,8 x 6,6 mm) Arrays typically of 768 x 480 or more 1388 x 1040 (1,4 megapixels) Size of pixel 6,45µm x 6,45µm

9 Other chips CCD Charge coupled device EMCCD Electron Multiplying CCD ICCD Intensified CCD EBCCD Electron bombardment CCD Back-illuminated CCD CMOS Complementary Metal Oxide Semiconductor

10 Dynamic range full well capacity DR = Total noise (in the dark) Full well capacity The number of electrons that each pixel of a chargecoupled device can hold without overflowing and causing blooming. Noise Dark current

11 Linearity Relationship between incoming light and output signal Critical to ratio calculations Linear sensor range of zero to full well capacity would be ideal Cooled cameras to minimize dark current Large full well capacity

12 Color camera This is what I saw. B&W camera This I want to analyze.

13 Color camera Transmitted light imaging Multiple fluorochromes per exposure Detecting autofluorescence

14 Bayer filter Each pixel is filtered to record only one color 50% green 25% red 25% blue

15

16

17 Zeiss Axiocam HRc Relative Spectral Sensitivity Please see Zeiss brochure for the Zeiss Axiocam HR camera. Web address below: 1.4 megapixel CCD sensor array 14 bit color depth RGB sensor

18 B&W camera Sensitivity and resolution In fluorescent imaging you are already using one detection filter, why use a second?

19 Zeiss Axiocam HRm Relative Spectral Sensitivity Please see Zeiss brochure for the Zeiss Axiocam HR camera. Web address below: Same stats as HRc without color filtering Long wavelengths High sensitivity

20 Bit depth Bit depth Steps A/D converter steps Range of CCD and range of A/D converter = How many electrons per step

21 Exposure Exposure from photometric luminance and exposure time: E = L t Acquisition quality E.g. Dynamic range fully in use Special need in fluorescence imaging: Exposure time must not exceed bleaching level!

22 Histograms

23 Binning Combination of multiple adjacent pixels to form one brighter pixel Brighter signal with same exposure time but loss of resolution 3x3 binning 2x2 binning

24

25 Color co-site sampling Please see Zeiss brochure for the Zeiss Axiocam HR camera. Web address below:

26 Microscanning Please see Zeiss brochure for the Zeiss Axiocam HR camera. Web address below:

27 Sampling frequency For microscope: shortest resolvable distance (λ/2*na) Abbe s equation For camera: Number of horizontal pixels / width of imaging area = Horizontal sampling frequency Nyquist theorem: fs > 2 f(max) In microscopy f(max) usually determined by optical resolution of the microscope Shortest resolvable distance must be scanned with at least two pixels for maximum resolution

28

29 Automation Filter / objective change Camera Auto exposure Motorized stage (x-y-z) Cell culture environment Auto focus

30 Scaling Microscope programs have data of all used microscope optics and camera Size data available from program Scale bar

31 Live Cell Imaging Cell culture conditions Fast camera cycle Electronic shutters Short exposure time High sensitivity Image frames combined to video Analyzed as stacks of images

32

33 Possibilities Quantitative data Automated acquisition and analysis Can handle lots of images Statistics Live cells Not just endpoints

34 Further information Optical Microscopy Primer: The Photonics Dictionary

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