Using CMOS Cameras for Light Microscopy
Table 1: Comparison of the number of experimental images that must be captured and averaged with CMOS and CCD cameras to achieve the same noise reductions.
CCD
Noise Reduction Relative to
Single Image 5×
5.5× 6×
6.5×
Number of Samples Averaged
25 30 36 42
CMOS
Number of Samples Averaged
26 33 39 46
When multiple experimental images are averaged, oſten
to reduce the noise to make the image clearer or reduce the error bars on a measurement, the noise is expected to decrease by the square root of the number of images averaged for random Gaussian noise. However, as Table 1 demonstrates, the telegraph noise causes the averaging of CMOS data to be less effective than for a scientific CCD with Gaussian read noise. Te noise reductions in Table 1 were obtained as follows.
Two stacks of the same number of bias images were obtained, and each stack was averaged. Te two average images were then subtracted from each other so that only camera read noise remained as the dominant noise source. Te standard deviation, that is, read noise, across this subtracted average image was measured and divided into the standard deviation from a single subtracted image to calculate noise reduction relative to a single image (images not shown). In each row it is apparent that the number of CMOS sample images needed to reduce the noise by the given amount is more than the CCD. Although it is not realistic in many situations to acquire more than 25 images of the same cell due to photobleaching and dynamic cellular changes, CMOS cameras’ non-Gaussian read noise would also add variation to the intensity measured even for a single acquisition on a single cell. Terefore, when averaging the intensities from several cells (as is oſten done in many scientific cell imaging studies) to reduce this variation (and its associated error bars) to distinguish, for example, an experimental sample from a control sample, the noise reduction for a CMOS would still be less effective than a CCD. Simply
put, when trying to distinguish similar signals by reducing noise through averaging many experimental samples, a few more images and/or experiments may be needed when using a CMOS camera. Tis would only be an issue when the research outcomes require differentiation of very small differences in signal. In such scenarios it may be of value to continue to use CCD technology.
Conclusion Te advancement of consumer electronics toward
smaller, cheaper, and more portable devices has led to CMOS cameras capable of scientific biological imaging alongside standard CCDs. Tis is a significant technological offering for bio-imaging as it is available for approximately half the cost of performance microscopy CCD cameras with the added benefit of faster frame rates. Te smaller pixel size in CMOS chips allow them to be used with lower magnifications while still adequately sampling to achieve increased signal and field of view, comparable with CCDs. Scientific-grade CMOS cameras do display random telegraph noise speckling absent in CCDs, which can increase the number of experimental samples needed for noise reduction. However, CMOS cameras are also capable of higher frame rates. Tis similar SNR response and high speed allows CMOS cameras to compete in medium light microscopy tasks where some noise is acceptable, such as motility, brightfield, and fluorescent protein imaging and time-course experiments.
References [1] J Janesick, Scientific Charge-coupled Devices, SPIE Press, Bellingham, Washington, 2001.
[2] J Joubert and D Sharma, Photon Spectra 44(3) (2011) 46–50.
[3] Y Sabharwal, Microscopy and Analysis 25(4) (2011) S5–S8.
[4] H Shroff, C Galbraith, J Galbraith, and E Betzig, Nature Methods 5 (2008) 417–23.
[5] P Martin-Gonthier, E Havard, and P Magnan, Electronics Letters 46(19) (2010) 1323–24.
[6] X Wang, P Rao, A Mierop, and A Teuwissen, IEDM Technical Digest (2006) 115–18.
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