• Place a power meter sensor on the microscope stage.

• Center the sensor and the objective.

• Zero the sensor to ensure accurate readings.

• Select the wavelength of the light source you want to monitor, using your power meter controller or associated software.

• Turn on the light source and immediately record the power output over time until it stabilizes.

  I personally use the Thorlab Powermeter Software in Monitoring mode and record every 10 seconds for 24 hours and stops (recording) when it has been stable for 1 h.
  

• Save the recorded data as a CSV file.
• Repeat for each light source.
  

  Keep the light source turned on at all times. Depending on your hardware, the light source may remain continuously on or be automatically shutdown by the software when not in use.

• Use the provided spreadsheet template, Illumination_Warmup Kinetic_Template.xlsx
• Copy and paste the data from the recorded CSV file into the highlighted cells of the template to visualize your results.
• For each light source, plot the measured power output (in mW) against time to analyze the data.

• Calculate the relative power using the formula: Relative Power = (Power / Max Power) for each wavelength. Then, plot the Relative Power (%) against Time to visualize the data.

We observe some variability in the power output during the first 20 min. It is especially noticeable for the 385 nm light source.

To assess the stability:

• Define a Stability Duration Window: This is a time period (e.g., 10 minutes) during which the power output should remain stable.

• Specify a Maximum Coefficient of Variation (CV) Threshold: This a limit acceptable for the CV (e.g., 0.01%).

• Calculate the Coefficient of Variation (CV): CV = (Standard Deviation / Mean)

• Plot the calculated CV over time to analyze the stability of the power output.

We observe that most of light sources stabilize quickly, within less than 10 minutes, while the 385 nm light source takes approximately 41 minutes to reach the stability threshold. The template also calculates Stability Factor (S) using the formula: S (%) = 100 × (1 - (Pmax - Pmin) / (Pmax + Pmin))

• Report the results in a table

The illumination warmup time for this instrument is approximately 40 minutes. This duration is essential for ensuring accurate quantitative measurements, as the Coefficient of Variation (CV) threshold is strict, with a maximum allowable variation of 0.01% within a 10-minute window.

• Warm up the light sources for the required duration (see previous section).
• Place the power meter sensor on the microscope stage.
• Center the sensor and the objective.
• Zero the sensor to ensure accurate readings.
• Select the wavelength of the light source you want to monitor, using your power meter controller or associated software.
• Turn the light source on to 100% power.
• Record the average power output over 10 seconds.
  I personally re-use the data collected during the warm-up kinetic experiment (when the power has been stable for 1h) for this purpose.
• Repeat for each light source.
  

• Use the provided spreadsheet template Illumination_Maximum Power Output_Template.xlsx
• Fill in the highlighted cells of the template to visualize your results.
• For each light source, plot the measured Maximum Power Output (in mW).

These results are informative on their own but could become even more meaningfull when comapred to the manufacturer’s specifications.

• Calculate the Relative Power_Spec using the formula: Relative Power_Spec = (Measured Power / Manufacturer Specifications) and plot the Relative Power for each light source.

• Report the results in a table

This instrument provides 80% of the power specified by the manufacturer. These results are consistent, as the manufacturer’s specifications are based on a different objective, and likely different filters and mirrors, which can affect the measured power output.

• Warm up the light sources for the required duration (see previous section).
• Place the power meter sensor on the microscope stage.
• Center the sensor and the objective.
• Zero the sensor to ensure accurate readings.
• Select the wavelength of the light source you want to monitor, using your power meter controller or associated software.
• Turn the light source on to 100% power.
• Record the power output every 100 ms for 1 minute. For some microscope dedicated to a fast imaging it might be required to record stability at a faster rate. The Thorlab S170C sensor can record at 1 kHz !
  

  I personally acquire this data immediately after the warm-up kinetic experiment, without turning off the light source.

• Repeat for each light source.

• Use the provided spreadsheet template Illumination_Stability_Template.xlsx
  
• Copy and paste the data from the recorded CSV file into the highlighted cells of the template to visualize your results.
• For each light source, plot the Measured Power Output (in mW) over Time.

• Calculate the Relative Power using the formula: Relative Power = (Power / Max Power). Then, plot the Relative Power (%) over Time.

• Calculate the Stability Factor (S) using the formula: S (%) = 100 × (1 - (Pmax - Pmin) / (Pmax + Pmin)).
• Calculate the Coefficient of Variation (CV) using the formula: CV = Standard Deviation / Mean.
• Reports the results in a table.

From the Stability Factor results, we observe that the difference between the maximum and minimum power is less than 0.03%. Additionally, the Coefficient of Variation indicates that the standard deviation is less than 0.004% of the mean value, demonstrating excellent realtime power stability.

The light sources exhibit a very high stability, >99.9% during a 1-minute period.

• Warm up the light sources for the required duration (see previous section).
• Place the power meter sensor on the microscope stage.
• Center the sensor and the objective.
• Zero the sensor to ensure accurate readings.
• Select the wavelength of the light source you want to monitor, using your power meter controller or associated software.
• Turn the light source on to 100% power.
• Record the power output every 10 seconds for 15 minutes.

  I personally re-use the data collected during the warm-up kinetic experiment (when the power has been stable for 1h) for this purpose.

• Repeat for each light source you.

• Use the provided spreadsheet template Illumination_Stability_Template.xlsx
  
• Copy and paste the data from the recorded CSV file into the highlighted cells of the template to visualize your results.
• For each light source, plot the Measured Power Output (in mW) over Time.

• Calculate the Relative Power using the formula: Relative Power = (Power / Max Power). Then, plot the Relative Power (%) over Time.

• Calculate the Stability Factor (S) using the formula: S (%) = 100 × (1 - (Pmax - Pmin) / (Pmax + Pmin)).
• Calculate the Coefficient of Variation (CV) using the formula: CV = Standard Deviation / Mean.
• Reports the results in a table.

From the Stability Factor, we observe that the difference between the maximum and minimum power is less than 0.01%. Additionally, the Coefficient of Variation indicates that the standard deviation is less than 0.004% of the mean value, demonstrating excellent short-term power stability.

The light sources exhibit high stability, maintaining >99.9% stability during a 15-minute period.

• Warm up the light sources for the required duration (see previous section).
• Place the power meter sensor on the microscope stage.
• Center the sensor and the objective.
• Zero the sensor to ensure accurate readings.
• Select the wavelength of the light source you want to monitor, using your power meter controller or associated software.
• Turn the light source on to 100% power.
• Record the power output every 10 seconds for 1 hour.

  I personally re-use the data collected during the warmup kinetic experiment.

• Repeat for each light source
  

• Use the provided spreadsheet template Illumination_Stability_Template.xlsx
  
• Copy and paste the data from the recorded CSV file into the highlighted cells of the template to visualize your results.
• For each light source, plot the Measured Power Output (in mW) over Time

• Calculate the Relative Power using the formula: Relative Power = (Power / Max Power). Then, plot the Relative Power (%) over Time.

• Calculate the Stability Factor (S) using the formula: S (%) = 100 × (1 - (Pmax - Pmin) / (Pmax + Pmin)).
• Calculate the Coefficient of Variation (CV) using the formula: CV = Standard Deviation / Mean.
• Reports the results in a table.

From the Stability Factor, we observe that the difference between the maximum and minimum power is less than 0.03%. Additionally, the Coefficient of Variation indicates that the standard deviation is less than 0.02% of the mean value, demonstrating excellent mid-term power stability.

The light sources exhibit exceptional stability, maintaining a performance of >99.9% during a 1-hour period.

• Warm up the light sources for the required duration (see previous section).
• Place the power meter sensor on the microscope stage.
• Center the sensor and the objective.
• Zero the sensor to ensure accurate readings.
• Select the wavelength of the light source you want to monitor, using your power meter controller or associated software.
• Turn the light source on to 100% power.
• Record the average power output over 10 seconds.
  I personally re-use the data collected for the maximal power output section and plot it over time.
• Repeat for each light source.

• Use the provided spreadsheet template Illumination_Long-Term_Stability_Log.xlsx
  
• Copy and paste the data from the recorded CSV file into the highlighted cells of the template to visualize your results.
• For each light source, plot the Measured Power Output (in mW) over Time

• Calculate the Relative Power using the formula: Relative Power = (Power / Max Power). Then, plot the Relative Power (%) over Time.

• Calculate the Relative Power_Spec by comparing the measured power to the manufacturer’s specifications using the following formula: Relative Power_Spec = Power / Power_Spec
• Plot the Relative Power_Spec (% Spec) over Time.

We expect a gradual decrease in power output over time due to the aging of hardware. Light sources should be replaced when the Relative Power_Spec falls below 50%.

• Reports the results in a table.

• Keep the Log file to append future measurements

The light sources are somehow stable over the last 2 years but a decrease in the maximum power output is seen.

• Warm up the light sources for the required duration (see previous section).
• Place the power meter sensor on the microscope stage.
• Center the sensor and the objective.
• Zero the sensor to ensure accurate readings.
• Select the wavelength of the light source you want to monitor, using your power meter controller or associated software.
• Adjust its intensity to 100%, then incrementally decrease the intensity input increase to 90%, 80%, 70%, and so on, until 0%.
  I typically collect this data immediately after the warm-up kinetic phase and once the real-time power stability data has been recorded.
• Record the power output corresponding to each input level.
• Repeat for each light source

• Use the provided spreadsheet template Illumination_Linearity_Template.xlsx
  
• Enter your measurement into the highlighted cells of the template to visualize your results.
• For each light source, plot the Measured Power output (in mW) as a function of the Input (%).

• Calculate the Relative Power using the formula: Relative Power = Power / MaxPower.
• Plot the Relative Power (%) as a function of the Input (%).

• Determine the equation for each curve, which is typically a linear relationship of the form: Output = K × Input
• Report the Slope (K) and the Coefficient of Determination (R²) for each curve in a table.

The slopes demonstrate a nearly perfect linear relationship between the input and the measured output power, with values very close to 1. The coefficient of determination (R²) indicates a perfect linear fit, showing no deviation from the expected relationship.

The light sources are highly linear with an average Slope=0.999 and a perfect fit R²=1

• Warm up the light sources for the required duration (see previous section).
• Place the power meter sensor on the microscope stage.
• Center the sensor and the objective.
• Zero the sensor to ensure accurate readings.
• Select the wavelength of the light source you want to monitor, using your power meter controller or associated software.
• Turn on the light source to 100% intensity.
• Record the power output for each objective, as well as without the objective in place.

  I typically collect this data after completing the warm-up kinetic phase, followed by the real-time power stability measurements, and immediately after recording the power output linearity.

• Repeat for each light source and wavelength

• Use the provided spreadsheet template Objective and cube transmittance_Template.xlsx
  
• Enter your measurement into the highlighted cells of the template to visualize your results.
• For each light source, plot the Measured Power output (in mW) as a function of the wavelength (in nm).

• Calculate the Relative Transmittance using the formula: Relative Transmittance = Power / Power_NoObjective.
• Plot the Relative Transmittance (%) as a function of the wavelength (in nm).

• Calculate the average transmittance for each objective
• Compare the average transmittance to the specifications provided by the manufacturer
• Report results in a table.

The measurements are generally close to the specifications, with the exception of the 63x-1.4 objective. This deviation is expected, as the 63x objective has a smaller back aperture, which reduces the amount of light it can receive..

The objectives are transmitting light properly.

• Warm up the light sources for the required duration (see previous section).
• Place the power meter sensor on the microscope stage.
• Center the sensor and the objective.
• Zero the sensor to ensure accurate readings.
• Select the wavelength of the light source you want to monitor, using your power meter controller or associated software.
• Turn on the light source to 100% intensity.
• Record the power output for each filter cube.

  I typically collect this data after completing the warm-up kinetic phase, followed by the real-time power stability measurements, and immediately after recording the power output linearity.

• Repeat for each light source and wavelength

• Use the provided spreadsheet template Objective and cube transmittance_Template.xlsx
  
• Enter your measurement into the highlighted cells of the template to visualize your results.
• For each light source, plot the Measured Power output (in mW) as a function of the wavelength (in nm)..

• Calculate the Relative Transmittance using the formula: Relative Transmittance = Power / Power_MaxFilter.
• Plot the Relative Transmittance (%) as a function of the wavelength (in nm).

• Calculate the Average Transmittance for each filter at the appropriate wavelengths
• Report the results in a table.

• The DAPI cube transmits only 14% of the excitation light compared to the Quad Band Pass DAPI/GFP/Cy3/Cy5. While it is still usable, it will provide a low signal. This is likely because the excitation filter within the cube does not match the light source properly. Since an excitation filter is already included in the light source, the filter in this cube could be removed.

• The GFP and DsRed cubes transmit 47% of the excitation light compared to the Quad Band Pass DAPI/GFP/Cy3/Cy5, and they are functioning properly.

• The DHE cube does not transmit any light from the Colibri. This cube may need to be removed and stored.

• The Cy5 cube transmits 84% of the excitation light compared to the Quad Band Pass DAPI/GFP/Cy3/Cy5, and it is working properly.

Actions to be Taken:

• Remove the excitation filter from the DAPI cube, as it does not properly match the light source and is redundant with the excitation filter already included in the light source.
• Remove and store the DHE cube, as it does not transmit any light from the Colibri and is no longer functional.

1. Place a fluorescent plastic slide (Thorlabs FSK5) onto the stage.
2. Center the slide and the objective.
3. Adjust the focus to align with the surface of the slide.
   

   I typically use a red fluorescent slide and focus on a scratch mark on its surface for alignment.

4. Slightly adjust the focus deeper into the slide to minimize the visibility of dust, dirt, and scratches.

5. Modify the acquisition parameters to ensure the image is properly exposed.

   I typically use the auto-exposure feature, aiming for a targeted intensity of 30%.

6. Capture a multi-channel image.
7. Repeat steps 5 and 6 for each objective and filter combination.

You should have acquired several multi-channel images that now need processing to yield meaningful results.

I initially was using the Field Illumination analysis function of the MetroloJ_QC plugin for FIJI but eventually branched away to write my own processing plugin named QC Scope. For more information about the QC Scope please refer to the QC Scope repository on Github. For more information about MetroloJ_QC plugin please refer to manual available on the MontpellierRessourcesImagerie repository on GitHub.

1. Open FIJI.
2. Launch the QC Scope Toolbar by navigating to Plugins>QC Scope>QC Scope Toolbar.
3. Click on Uniformity.
   1. If one or more images are already opened QC Scope will process them.
   2. If no image is open, QC Scope will prompt to select a folder and process all images withing the folder (and subfolders)
      

      QCSCope file format compatibility

      For now, QC Scope only processes images with the following extensions  ".tif", ".tiff", ".jpg", ".jpeg", ".png", ".czi", ".nd2", ".lif", ".lsm", ".ome.tif", ".ome.tiff"

4. QC Scope will try to read the Metadata from the first image and pre-process all the channels with default or the last used processing settings
5. It will display the metadata, the initial results and the processing options in a dialog
   1. Microscope Metadata: Objective Magnification, NA, and Immersion media
   2. Image Calibration status, Pixel Width, Height, Voxel Size, Unit
   3. For each channel: Name and Emission Wavelength
   4. Processing Settings:
      1. Binning Method:
         1. Iso-Density (preferred): This method divides the image into 10 bins of equal Nb of Pixels. Nb Pixel Per Bin = (Width x Height) / 10 and assign a new pixel value of 25 for all the Nb Pixel Per Bin darkest pixels, 50 for the next darkest Nb Pixel Per Bin etc... until 250 for the brightest Nb Pixel Per Bin pixels.
         2. Iso-Intensity: This method divides the image into 10 bins of equal bin intensities. Bin Width = (Max - Min) / 10 and assign a new pixel value of 25 for all the pixels with an intensity between Min and Min + Bin With, 50 for intensities between Min + Bin Width and Min + 2 x Bin Width etc... until 250 for intensities between Min + 9 x Bin Width and Max.
      2. Gaussian Blur: Apply a gaussian blur with the given Gaussian Blur Sigma before processing the image channel
      3. Channel: The selected channel will be processed with the entered processing parameters and displayed as part of the testing process to define optimal processing parameters.
      4. Batch Mode: If activated, QC Scope will re-use the settings without displaying the dialog unless metadata differs
      5. Save Individual Files: For each image, QC Scope will save the individual processed images (1 per channel) and a CSV file with all measured parameters.
      6. Prolix Mode: Display all the QC Scope actions in the Log

      7. Test Processing: When selected the Dialog will keep appearing. This is useful to test the Processing Settings
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         

6. QC Scope will save files in a folder named Output on your desktop:

   1. At least 2 CSV files:

      1. Field Uniformity_All-Data_Merged.csv gathers all the measured parameters

      2. Field Uniformity_Essential-Data_Merged.csv gathers only the essential information

   2. Optionnally, if Save Individual Files is selected QC Scope will also save:
      1. 1 CSV file per image NameOfYourImage_Uniformity-Data.csv with one row per channel containing all the measured parameters
      2. 1 TIF file per channel for every processed image showing the binned (Iso-density or Iso-Intensity) image map with the Reference Center indicated as an overlay

Note: QC Scope never overwrites files. It will check for the existence of files and increment a number until it can safely write the output file.

Description of QC Scope Field Uniformity Results (in bold the results included in Essential Data)

Plot the uniformity and centering accuracy for each objective.

 Plot the uniformity and centering accuracy for each filter set. 

This specific instrument has a quad-band filter as well as individual filter cubes. We can plot the uniformity and centering accuracy per filter types. 

The uniformity and centering accuracy are excellent across all objectives and filters, consistently exceeding 90%. However, the single-band filter cubes exhibit slightly lower uniformity and centering accuracy compared to the quad-band filter cube.

1. Place 4 µm diameter fluorescent beads (TetraSpec Fluorescent Microspheres Size Kit, mounted on a slide) on the microscope stage.

2. Center an isolated bead under a high-NA dry objective.

3. Crop the acquisition area to only visualize one bead but keep it large enough to anticipate a potential drift along the X and Y axes (100 um FOV should be enough)
   

4. Select an imaging channel appropriate for the fluorescent beads

   I typically use the Cy5 channel which is very bright and resistant to bleaching, yet this channel has a lower resolution, but it does not really matter here

5. Acquire a large Z-stack at 1-minute intervals for a duration of 24 hours.

   To ensure accurate measurements, it is essential to account for potential drift along the Z-axis by acquiring a Z-stack that is substantially larger than the visible bead size. I typically acquire a 40 µm Z-stack.
   

1. Open your image in FIJI
2. If necessary, crop the image to focus on a single bead for better visualization.
3. Use the TrackMate plugin included in FIJI to detect and track spots over time Plugins\Tracking\TrackMate.
4. Apply Difference of Gaussians (DoG) spot detection with a detection size of 4 µm
5. Enable sub-pixel localization for increased accuracy
6. Click Preview to visualize the spot detection
7. Set a quality threshold (click and slide) high enough to detect a single spot per frame
8. Click Next and follow the detection and tracking process
9. Save the detected Spots coordinates as a CSV file for further analysis

• Open the spreadsheet template XYZ Drift Kinetic_Template.xlsx and fill in the orange cells.
• Copy and paste the XYZT and Frame columns from the TrackMate spots CSV file into the corresponding orange columns in the spreadsheet.
• Enter the numerical aperture (NA) and emission wavelength used during the experiment.
• Calculate the relative displacement in X, Y, and Z using the formula: Relative Displacement = Position - Position_Initial.
• Finally, plot the relative displacement over time to visualize the system's drift.

Identify visually the time when the displacement is lower than the resolution of the system. On this instrument it takes 120 min to reach its stability. Calculate the velocity, Velocity = (Displacement₂-Displacement₁)/T₂-T₁) and plot the velocity over time.

Calculate the average velocity before and after stabilisation and report the results in a table.

The warmup time for this instrument is approximately 2 hours. After the warmup period, the average displacement velocity is 14 nm/min, which falls within an acceptable range.

1. Place 4 µm diameter fluorescent beads (TetraSpec Fluorescent Microspheres Size Kit, mounted on a slide) on the microscope stage.

2. Center an isolated bead under a high-NA dry objective.

3. Crop the acquisition area to only visualize one bead but keep it large enough to anticipate a potential drift along the X and Y axes (100 um FOV should be enough)
   

4. Select an imaging channel appropriate for the fluorescent beads

   I typically use the Cy5 channel which is very bright and resistant to bleaching, yet this channel has a lower resolution.

5. Acquire a Z-stack at positions separated by 0 um (Drift), 1000 um and 10 000 um in both X and Y direction.

6. Repeat the acquisition 20 times

7. Acquire 3 datasets for each condition

1. Open your image in FIJI
2. If necessary, crop the image to focus on a single bead for better visualization.
3. Use the TrackMate plugin included in FIJI to detect and track spots over time Plugins\Tracking\TrackMate.
4. Apply Difference of Gaussians (DoG) spot detection with a detection size of 4 µm
5. Enable sub-pixel localization for increased accuracy
6. Click Preview to visualize the spot detection
7. Set a quality threshold (click and slide) high enough to detect a single spot per frame
8. Click Next and follow the detection and tracking process
9. Save the detected Spots coordinates as a CSV file for further analysis

• Open the spreadsheet template Stage Repositioning_Template.xlsx and fill in the orange cells.
• Copy and paste the XYZT and Frame columns from the TrackMate spots CSV file into the corresponding orange columns in the spreadsheet.
• Enter the numerical aperture (NA) and emission wavelength used during the experiment.
• Calculate the relative position in X, Y, and Z using the formula: Relative Position_Relative = Position - Position_Initial.
• Finally, plot the relative position over time to visualize the system's stage repositioning dispersion.

We observe an initial movement in X and Y that stabilises. Calculate the displacement 2D Displacement = Sqrt( (X₂-X₁)² + (Y₂-Y₁)²) ) and plot the 2D displacement over time. Calculate the resolution of your imaging configuration, Lateral Resolution = Lambda_Emission / 2*NA and plot the resolution over time (constant).

This experiment shows a significant initial displacement between Frame 0 and Frame 1, ranging from 1000 nm to 400 nm, which decreases to 70 nm by Frame 2. To quantify this variation, calculate the dispersion for each displacement using the formula: Dispersion = StandardDeviation(Displacement). Report the results in a table.

The system has an effective Stage Repositioning Dispersion of 230 nm. The results are higher than expected because of the initial shift in the first frame that eventually stabilizes. Excluding the first frame significantly improves the measurements, reducing the repositioning dispersion to 40 nm. Further investigation is required to understand the underlying cause.

We observed a significant shift in the first frame, which was unexpected and invites further investigation. These variables can affect repositioning dispersion: i) Traveled distance, ii) Speed, iii) Acceleration, iv) Time, and v) Environment. We decided to test the first three.

Methodology

 Processing

 Repositioning Dispersion: Impact of Traveled Distance

Results

Conclusion

Repositioning Dispersion: Impact of Speed and Acceleration

Results

Conclusion

What about the initial shift ?

Right, I almost forgot about that. See below.

Results

Conclusion

1. Place 4 µm diameter fluorescent beads (TetraSpec Fluorescent Microspheres Size Kit, mounted on a slide) on the microscope stage.

2. Center an isolated bead under a high-NA dry objective.

3. Crop the acquisition area to only visualize one bead but keep it large enough to anticipate a potential chromatic shift along the XY and Z axes
   

4. Acquire a multi-channel Z-stack
   

   I usually acquire all available channels, with the understanding that no more than seven channels can be processed simultaneously. If you have more than 7 channels you can either split them into sets smaller or equal to 7 keeping one reference channel in all sets.
   

5. Acquire 3 datasets
   

6. Repeat for each objective

You should have acquired several multi-channel images that now need processing to yield meaningful results. To process them, use the Channel Co-registration analysis feature of the MetroloJ_QC plugin for FIJI. For more information about the MetroloJ_QC plugin please refer to manual available at the MontpellierRessourcesImagerie on GitHub.

1. Open FIJI.
2. Load your image by dragging it into the FIJI bar.
3. Launch the MetroloJ_QC plugin by navigating to Plugins > MetroloJ QC.
4. Click on Channel Co-registration Report.
5. Enter a Title for your report.
6. Type in your Name.
7. Click Microscope Acquisition Parameters and enter:
   1. The imaging modality (Widefield, Confocal, Spinning-Disk, Multi-photon) 
   2. The Numerical Aperture of the Objective used.
   3. The Refractive index of the imersion media. (Air: 1.0; Water 1.33; Oil: 1.515)
      
   4. The Emission Wavelength in nm for each channel.

8. Click OK

9. Click Bead Detection Options
   1. Bead Detection Threshold: Legacy
   2. Center Method: Legacy Fit ellipses

10. Enable Apply Tolerance to the Report and Reject co-registration ratio above 1.

11. Click File Save Options.

12. Select Save Results as PDF Reports.

13. Select Save Results as spreadsheets.

14. Select Save result images.
15. Select Open individual pdf report(s).

16. Click OK.

17. Repeat steps 4 through 16 for each image you have acquired

This will generate detailed results stored in a folder named Processed. The Processed folder will be located in the same directory as the original images, with each report and result saved in its own sub-folder.

The following script for R processes channel co-alignment results generated by MetroloJ_QC Channel Co-registration function Process Chanel Co-Registration Results.R.

To use it, simply drag and drop the file into the R interface. You may also open it with RStudio and Click the Source button. The script will:

• Prompt the user to select an input folder.
• Load all _results.xls files located in the selected folder and subfolder
  
• Process and merge all results generated by the MetroloJ_QC Channel Co-registration.
• Split the filenames using the _ character as a separator and create columns named Variable-001, Variable-002, etc. This will help in organizing the data if the filenames are formatted as Variable-A_Variable-B, for example.
• Save the result as Channel_Co-Registration_Merged-Data.csv in an Output folder on the user's Desktop

To use it, simply drop the script into the FIJI toolbar and click Run.

1. If images are already opened it will process them

2. If no images are opened it will prompt to select a folder and will process all images available in the folder and subfolders

3. It reads files metadata or load information from previously run instances

4. The first image is pre-detected and setttings are displayed in a dialog

5. The dialog will keep being displayed until the detection is properly done (1 spot per channel)

6. Once the detection is correct it will compute the channel registration information
7. Data is saved as CSV files Channel-Registration_Essential-Data_Merged and Channel-Registration_Full-Data_Merged in an Output directory on the user desktop
8. In batch mode the settings set up for the first image are re-used for subsequent images unless discrepency is found or detection fails

The following spreadsheet provides a dataset that can be manipulated with a pivot table to generate informative graphs and statistics Channel_Co-registration_Template.xlsx.

Let's look at the 3D Colocalization Ratio for all pairs of channels.

For the 2x Objective we see that the 3D Colocalization Ratio is above 1 for the DAPI x GFP and DAPI x Cy5 pairs. This indicates that the chromatic shift is higher than the effective resolution of the system. Correction should be applied to images after acquisition. It somethimes possible to correct it before acquisition directly in the acquisition software. The correction values are provided by the Pixel Shift tables. Values highlighted correspond to a 3D Colocalization Ratio above 1.

These results shows a widefield instrument using a quadband pass filter: A single cube filtering 4 wavelengths. This instrument also possess individual filter cubes. Obviously the Colocalization Ratio are higher because of the mechanical shift induced by the filter turret.

With the corresponding Pixel Shift Table

Why should you care? Well when you are acquiring a multi-channel image you might see a significant shift between the two channels. This is particularly true for the combination of DAPI and Cy3 channels with the 10x Objective.

Report the Pixel Shift Table For each objective and each filter combination. This table can (should) be used to correct a multi-channel image by displacing the Channel 2 relative to the Channel 1 by the XYZ pixel coordinates indicated.