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Time-lapses are images taken at regular intervals over time. They are a very powerful method to illustrate biological processes such as cell division, bacterial growth... They are almost exclusively done on live samples kept in appropriate conditions.
The key variables for microscope timelapses are reviewed here
Sample preparation – How the sample is mounted, labeled, or stained
Temperature & environment – For live samples, conditions like temperature, humidity, and CO₂ levels affect biological processes
Time interval and duration – How often images are captured and the total length of imaging to capture the full process of interest
Imaging settings (magnification, illumination, detection) – Determines the level of detail visible (resolution vs field of view, illumination intensity, exposure time, photo-toxicity...)
Focus & stability – The sample must be and stay in focus for the full duration.
To come
To come
The time interval (or acquisition frequency) between images depends on the event you want to observe. According to the Nyquist-Shannon theorem, to capture a process without losing information, you must sample at least twice as fast as the highest frequency of the event.
Example: Imagine observing a bicycle wheel rotating at 1 turn per second:
If you look once per second, the valve always appears in the same position—you wouldn’t even notice the wheel is turning.
If you look twice per second, you see the valve in its original position and on the opposite side. You know the wheel is turning, but not the direction.
If you look more than twice per second, you can accurately determine both the wheel’s speed and direction.
Going back to timelapse microscopy for example with bacterial division (e.g., E. coli), which occurs roughly every 20 minutes, you should image at least once every 10 minutes. To be cautious and ensure nothing is missed, a 5-minute interval is often preferable.
The duration of your timelapse should be long enough to capture the entire process you want to study, including what happens before and after it occurs.
Imaging should be done more than 2 times faster than the faster event you want to detect. |
To come
Phototoxicity is the most critical factor to control during a time-lapse experiment. While it is negligible in brightfield imaging, it becomes a major concern when fluorescence microscopy is used. Be sure to consult the comprehensive blog post dedicated to. |
After proper sample care (environmental control and minimizing phototoxicity), focus stability is likely the greatest challenge in time-lapse imaging. Most microscopes gradually lose focus over time. This phenomenon, known as drift, occurs naturally due to gravity, thermal fluctuations, and mechanical relaxation. Drift can be particularly pronounced shortly after the instrument is switched on. For important time-lapse experiments, it is strongly recommended to turn on the microscope at least 2-3hours in advance to allow the system to warm up and reach thermal equilibrium before starting your time-lapse experiment.
To address this issue, many microscopes incorporate laser-based focus stabilization systems that continuously measure the distance between the objective and the sample. These measurements are used to automatically compensate for axial drift during acquisition. Although the underlying principle is similar, manufacturers use different names for this technology:
Perfect Focus (Nikon)
TrueFocus (Evident / Olympus Corporation)
Definite Focus (Zeiss)
Adaptive Focus Control (Leica Microsystems)
PureFocus (Prior Scientific)
fCRISP Autofocus System (Applied Scientific Instrumentation)
Regardless of the name, these systems rely on periodic measurements of the objective–sample distance to compensate for naturally occurring drift and maintain consistent focus throughout long acquisitions. Any timelapse experiment should use a hardware-based autofocus or focus stabilization system whenever available to maintain a constant objective–sample distance and ensure stable focus throughout long-term imaging.

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We strongly recommend to save raw acquisition files during acquisition using the proprietary format from the acquisition software. You can then use FIJI to open and process it. While scientific analysis must be performed on raw data, timelapses are also used to illustrate a process. For that purposes, timelapse can be processed to improve portability, compress size, better interoperability etc... We will provide some clues here to that purposes.
Not sure what is FIJI? Feel free to check our Microscopy software list to learn more. You will likely need ImageJ/FIJI, VLC media player and Handbrake. |
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Raw data file
1024 x 1022 16-bit 9601 frames -> 19.6 GB !
In an image each pixel is storing an information relative to brightness (for greyscale images). This information is usually an integer between 0 and X. The higher X, the higher number of possible values can be address to that pixel and thus the higher storage space is required to store this number. This is called bit-depth. A 8-bit image can store 255 value for each pixel. a 16-bit image can store 65000 values for each pixel etc... unfortunately human eyes are not able to appreciate more than few dozen of grey level. So reducing bit-depth is a easiest way to reduce the size of your data with actually changing how the images look.
In FIJI:
Drop the raw image file into the FIJI bar to import it
Select Image>Adjust>Brightness and contrast to open the Brightness and Contrast windows (Crtl+Shift+C)
Click Auto or adjust the brightness and contrast how you like it
Select Image>Type>8-bit to convert your image into 8-bit format (for multicolor images you should use RGB instead)
How many shades of grey can you identify? Please test yourself here by selecting ALL the squares that do not match the background. You need to submit your answers 8 times to get your result. My best was 42... |
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1024 x 1022 8-bit 9601 frames -> 9.8 GB
Cropping your image to your region of interest will effectively reduce the file size without affecting your resolution.
In FIJI:
Click on the rectangle selection tool
Click and drag while maintaining the shift key (this key will lock the aspect ratio 1:1 : square) around your region of interest
Select Image>Crop to crop your image (Crtl+X)
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Cropped to 900 x 900 8-bit 9601 frames -> 7.6 GB
Another option consist in resizing (downsizing) your image. This means converting a number of pixel to a smaller number which effectively reduce the file storage size but also the resolution.
In FIJI:
Image>Adjust>Size...
Check the following settings:
Constrain aspect ratio
Average when downsizing
Interpolation: Bicubic
Enter the number of pixel for the height
500 for web usage
720 for presentation
1080 for full HD
Click OK
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900 x 900 downsized to 500 x 500 8-bit 9601 frames -> 2.3 GB
To come
Sometimes the brightness of the images can vary over time. This can be due to the sample itself (bleaching, etc), but also from the detector (camera). Most of the time it comes from the light source.
It is possible to perform a brightness correction. I haven't find a tool that do that natively but a short script can help.
// ------------------------------------------------------------
// Brightness normalization of each slice in a stack
// Each slice is scaled so its mean intensity equals "target"
// ------------------------------------------------------------
// ---- USER SETTINGS ----
target = 128; // Desired mean intensity (0–255 for 8-bit)
// ---- Convert to 32-bit for precise calculations ----
run("32-bit");
// Get number of slices
n = nSlices;
// Loop through all slices
for (i = 1; i <= n; i++) {
setSlice(i);
// Get full statistics: area, mean, min, max, std
getStatistics(area, mean, min, max, std);
// ---- Safety check: avoid division by zero ----
if (mean == 0) {
print("Warning: Slice " + i + " has mean = 0. Skipping normalization.");
continue; // Skip this slice
}
// Calculate scaling factor
factor = target / mean;
// Optional warning if scaling may cause clipping after 8-bit conversion
if (max * factor > 255) {
print("Warning: Slice " + i + " may clip after scaling.");
}
// Apply scaling
run("Multiply...", "value=" + factor);
}
// ---- Convert back to 8-bit ----
run("8-bit");
// Improve display scaling
run("Enhance Contrast", "saturated=0.35");
print("Normalization complete."); |
Make sure to run this macro on FIJI on the original image not adjusted for brightness and contrast
Timestamps are critical information because they indicate what is the real speed of the event that are being displayed. Without it, the observer has no idea if it is a fast process that is slowed down or vice-versa. Timestamps are usually stored within the raw file metadata, to read it:
In FIJI:
Image>Properties...
Look at the frame interval
(if it is not present you should complain to the company that has provided the acquisition software)
In the example the frame interval is 3 seconds.
In FIJI:
Image>Stacks>Series Labeler
Series Labeler is a very effective tool to write timestamps on the image. However it is writing the information on the image and thus distroying the data underneath...
An alternative is Time Stamper. Time stamper allows writing as an overlay but does not offer the preview option.
In FIJI:
Image>Stacks>Time Stamper
This will add the timestamps as an overlay (floating layer that is independent of your image). To write the overlay on the images, you may need to flatten the overlay. To do so in Fiji Image>Overlay>Flatten (Crtl+Shift+F)
900 x 900 downsized to 500 x 500 8-bit 9601 frames with timestamps labelled with Series Labeler
Reslicing is a process of reducing the number of frames in your timelapse file. This can be done in two ways:
In FIJI
Cropping in time does not affect the interval between frames so it can (and should) be done before adding timestamps labels
In FIJI
It is critical to keep in mind that reducing the overall number of frames increases the interval between frames. To avoid any problem you may use timestamps before reducing the overall number of frames to keep the information on the image itself.
You can (and should) encode your file in a video format for an easy visualization. Several options are available, my suggestions are:
Both are free open-source cross-platform video encoders. Handbrake has a user-interface whereas FFmpeg requires command lines.
Encoding with Handbrake
In the meanwhile we need to save our file into a that is compatible with Handbrake. To my knowledge only the AVI format is compatible.
In FIJI
In Handbrake
Some preset are already defined but for you might want to use a customized one that better fit your scientist needs:
Most if not all video files can be open and read with VideoLAN VLC: a free and open source cross-platform multimedia player.
To come later