In this on-demand SelectScience webinar, imaging expert Takeo Ogama, from Olympus Corporation of the Americas, covers the link between the biology and observed digital image data, the factor effects on signal intensity, causes of background noise and how to minimize them, trade-off factors that have an impact on image and data quality, and best practices for image acquisition.
These are the basics for widefield fluorescence imaging but could be leveraged for any biological experiment that uses a microscope and digital image acquisition.
Key learning objectives for this session include:
Read on for highlights from the live Q&A session:
TO: The “range of view” mentioned here is called field of view, which indicates how large a field we can observe. If you're using a field number 22 microscope system, you can observe a diameter of 22-millimeter field of view with 1x observation. If you're using 100x magnification objective, you can observe 220-micrometer diameter of field of view. This is the field of view and this is defined by field number. This is different from a numerical aperture (NA) mentioned in this presentation. Numerical aperture is the indicator, it shows how large of an angle we can use to gather light from your sample. As we indicated using the schematic figure, a higher number is better in general. NA decides resolution, lightness, field depth etc.
The second point is that if we observe a wider field of view, there is a trade-off in resolution. As we mentioned in the trade-off section, in general, if we use the same size chip and observe a smaller field of view, we can achieve higher resolution. If we use a lower magnification TV adaptor, we can observe a wider field of view but lose our resolution.
TO: It really depends on your application and sample. The fundamental differences between an industrial camera for machine vision and a camera designed for life science are dustproof level and expected sample brightness. Regarding the dustproof level, some industrial cameras don’t have the dustproof sealing in front of the sensor. An industrial camera doesn't need such dustproofing because the optics for machine vision cannot visualize tiny dust particles on the sensor. On the other hand, if you combine that camera with your microscope, the optics can visualize these fine dust particles on your sensor. Therefore, you need to make sure you use a camera with the appropriate cleanliness level.
As for the second point regarding the expected sample brightness, your biological fluorescence sample is much dimmer than an industrial sample. In industrial inspection, we can apply bright enough illumination to see dimmer samples. That means you need to ensure you test any industrial camera with your microscope and with your samples before purchasing them.
TO: In general, it is said that longer gentle excitation is better. In short, we need to avoid damaging your sample. The damage has two categories; phototoxicity and bleaching. Phototoxicity is damage on your biological sample which can change your sample's biological behavior and deteriorate cell biology and ability. It contains DNA damage through UV light or even permanent damage through ROS, reactive oxygen species. Bleaching is a permanent reduction of the fluorescence light intensity, this is also caused by ROS.
So, preventing the generation of ROS is really the key to prevention of damage. The best strategy is to reduce the probability of light absorption of excited fluorosphere. Because through that process, ROS is generated and could cause permanent destruction or change of binding with adjacent molecules. To reduce this probability, the best way is just to reduce the light density on your sample. Another strategy is to use an antifade reagent like an oxygen scavenger because, as always, the major damaging process is oxidation.
TO: The answer to this question is based on the intended purpose, e.g., how detailed do you need the resolution to be? How thin a section do you need? And how dim a sample do you want to observe? When utilizing a PMT to acquire images, the following factors apply:
Signal-to-noise ratio
Noise
A number of factors are unique to cameras, such as resolution, read-out noise, pixel-size and frame rate, so if you are using a PMT you don’t need to worry about these.
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