Probably the most important piece of metadata and the one that is usually needed first, is the scale factor. The scale factor tells us what area a pixel represents on our specimen.
d : dimension of a single pixel on the CCD/CMOS chip μm
b : binning (camera setting to aggregate several neighboring pixel) m: objective magnification
c : camera mount magnification
M: total magnification between sample and the camera
Note that for laser scanning confocal microscopes this formula does not apply as is, since the scanner of the instrument allows for arbitrary sampling areas (within the scanners capabilities) and the sampling density can vary. The easiest is to use the original files produced by the instrument (do not export tif, png or jpg) and to get the pixel size from the metadata. With ImageJ (Fiji), you can open most of the microscope formats using Menu > Plugins > Bio-Formats > Bio-Formats Importer. Usually the scale factor is already set correctly (check Menu > Analyze > Set Scale).
To do accurate measurements, it is essential to properly configure the instruments. If the sampling for a given experiment is not correct, there is little that can be done to salvage the measurement during the image processing.
The following paragraphs give an overview for the most important parameter, to consider while setting up an acquisition with a microscope.
The goal here is to spread the signal from our objects of interest over the entire dynamic range of our detector. To this end we want pixels considered background close to zero and the brightest object pixel just bellow the maximum value. Pixels we use later for measurements should not be underexposes nor saturated, in order to know the true value.
On the other hand, anything not considered an object of interest, e.g. specs of dust, can be outside of the detector range.
The Nyquist criterion, coming initially from signal processing (determined for 1D signals), serves as a guideline to determine the optimal pixel size (physical distance one pixel represents on the specimen).
A detailed explanation can be found on the SVI-wiki.
On the other hand objectives only can resolve so much detail. Having a pixel size far bellow the Rayleigh criterion for a given objective is also called over sampling. This means that despite having a very small pixel size, the objective will not be able to resolve additional information. Therefore oversampling usually results in creating redundant information, that does not achieve anything but to increase the data volume without additional information.
Abbe’s lateral resolution formula (x-y-resolution):
Abbe’s axial resolution formula (z-resolution)
NA: numerical aperture
Θ: half of the objective angular aperture
1.22 : Constant derived from Bessel functions
R : smallest resolved distance
When acquiring movies, there are two essential parameters, that will determine the accuracy of your measurements over time:
- frame rate (movie speed)
- observation time (duration of the movie)
To determine these parameter, it is a good strategy to acquire a movie at a high speed and over a long duration. Then by subsampling the video for frame rates and observation times, we can repeat the measurements and plot them against the frame rate/observation time.
For the frame rate, we usually will find this way a point where the measurement will start to fluctuate. Hence we need to choose a frame rate smaller than the one where we start to observe fluctuations.
For the observation time we can similarly observe a point where the variation of the measurement decreases. Once the variations of the measurements will converge on the standard measurement fluctuations we reached the point where the observation time is long enough to quantify the desired phenomenon.
Optimizing sampling parameter
In an ideal world, we would choose the optimal parameters of intensity, spacial and temporal sampling. But due to technical limitations (detector sensitivity, maximum frame rate, etc.) we often need to find the optimal compromise between feasibility and best possible sampling.
Bellow we have the trade-off circle of parameters. We also should keep an eye on the data volume produced during the acquisition.