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QC Scope is a plugin for FIJI designed to process  microscope images for Quality Control purposes.
Written by Nicolas Stifani from the Centre d'Innovation Biomédicale de la Faculté de Médecine de l'Université de Montréal.

Contents


Installation

  1.  for your operating system
  3. Unzip FIJI.app to your favorite location on your computer (usually your Desktop
  4. Start FIJI (aka FIJI.app, ImageJ-win.exe)
  5. Drag and drop QC_Scope.jar into the FIJI toolbar
  6. Click Save
  7. Click OK
  8. Close FIJI

  9. Reopen FIJI

After installation, QC Scope will be available in the FIJI menu under Plugins>QC Scope.

QC Scope Toolbar

The QC Scope floating toolbar is available for rapid and convenient access. To load it, click the QC Scope Toolbar in the FIJI menu under Plugins>QC Scope>QC Scope Toolbar.

QC Scope Auto-start

Additionally and for an even more convenient usage, it is possible to have the QC Scope Toolbar automatically loaded when FIJI is started. Click the Auto-start button or select the QC Scope Toolbar Auto-start in the FIJI menu under Plugins>QC Scope>QC Scope Toolbar Auto-start.

QC Scope Demo Images

For testing purposes, you will find  that can be used to process and generate results.

Additional information

QC Scope 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"

QC Scope file writing strategy

QC Scope never overwrites files. It checks for the existence of files and increment a number until it can safely write the output file without erasing data.

Filename Convention

If you are well organized when saving and naming your files, QC Scope will help you.
It specifically check for the presence of "_" in the filename and split it into Filename Variables.
For example if you label your image as Date_Microscope-A_Objective-X_Filter-Y_Condition-001.TIF QC Scope will provide in the output one column with each variable: Date, Microscope, Objective, Filter, Condition. Then you can use a Pivot Table in Excel to quickly access your data.

Field Uniformity

Usage

  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)
  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
  6. Check the metadata, the results and the binned image. If it looks good you can click OK. 

  7. 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
        Field Uniformity_All-Data_Merged.csv

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

    2. Optionally, if Save Individual Files is selected QC Scope will also save:
      1. 1 CSV file per image ImageName_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) map with the Reference Center indicated as an overlay

 

Example of iso-density image with the coordinates of the reference center.

 Settings

  • Microscope Settings read from the image metadata or from the preferences: Objective Magnification (character), NA (Numeric>0), and Immersion media 
  • Image Settings: Pixel Width (Numeric>0), Height (Numeric>0), Depth (Voxel) (Numeric>0), Unit (character). QC Scope uses standard space unit (nm, um, mm, cm, m, in, pixels) and will try to convert the entered value into on of those.
  • Channel Settings: For each channel: Name (character) and Emission Wavelength in nm ((Numeric>0)) as well as the source of the values
  • Processing Settings:
    • Binning Method:
      • 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.
      • 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.
    • Gaussian Blur: Apply a Gaussian blur with the given Gaussian Blur Sigma before processing each channel
    • 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.
    • Batch Mode: If activated, QC Scope will re-use the settings without displaying the dialog unless metadata differs
    • 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.
    • Prolix Mode: Display all the QC Scope actions in the log

    • Test Processing: When selected the QC Scope Field Uniformity Dialog will keep appearing. This is useful to test the Processing Settings. When you are satisfied you can uncheck Test processing to proceed to the next image.

 QC Scope Field Uniformity dialog

Metrics

 Field Uniformity measures how evenly illumination is distributed and how centered is the illumination across the field of view. The following metrics provide different perspectives on uniformity:

  1. Uniformity: Evaluates the overall evenness of illumination. Since a single value can't capture all variations, QC Scope computes several uniformity metrics for a comprehensive assessment.

    1. Standard Deviation (GV): The standard deviation of pixel intensities measures how much individual pixel values deviate from the mean intensity of the image. A low standard deviation indicates that the pixel intensities are close to the mean, suggesting high uniformity and minimal variation across the image. The standard deviation is in the same unit as the pixel intensity values in the image (Grey Value).

    2. Uniformity Std (%): Calculated as ratio between the intensities of the darkest and brightest pixels. This metric evaluates image uniformity by comparing the minimum pixel intensity to the maximum pixel intensity in the image. It ranges between 0 and 1. A value of 1 indicates perfect uniformity, where the minimum and maximum intensities are equal. This simple metric provides a quick indication of how evenly distributed the pixel intensities are. It highlights whether there are extreme intensity variations, such as bright or dark spots, which can suggest uneven illumination or artifacts. While easy to compute, this ratio is sensitive to outliers. A single very bright or very dark pixel can skew the measurement. It also does not take in account the distribution of pixel intensities and instead focuses on the minimun and maximum.
      In MetroloJ_QC, the Field Uniformity function applies a Gaussian blur before calculation. This reduce the impact of potential outliers. QC Scope uses the unmodified image to compute the Uniformity. For this reason QC Scope will always provide lower Uniformity Std values compared to MetroloJ QC as it is representing the worse case scenario.

      $$\text{Uniformity}_{Std} = \frac{\text{Min}}{\text{Max}}$$

       

    3. Uniformity Percentile (%): This metric evaluates image uniformity by analyzing the average intensities of the darkest and brightest pixels within a chosen percentile (e.g., 5%) instead of relying on extreme values. It uses the mean intensities of these percentile subsets to provide a more robust and representative measure of uniformity.

      $$\text{Uniformity}_{Percentile} = \left(1 - \frac{\text{Avg}_{95} - \text{Avg}_{5}}{\text{Avg}_{95} + \text{Avg}_{5}} \right)$$

    4. Coefficient of Variation (CV): The Coefficient of Variation is a standard statistical measure used to quantify the relative variation or dispersion of pixel intensities in an image. It is calculated as the ratio of the Standard Deviation to the Mean of the pixel intensities. The CV provides a dimensionless measure of variation, making it easier to compare variability across images with different intensity scales or ranges. It reflects the extent of variability in relation to the average intensity. A lower CV indicates higher uniformity, with pixel intensities tightly clustered around the mean. The CV adjusts for differences in intensity scale, enabling fair comparisons between images. It is particularly useful in imaging workflows where intensity levels may vary across samples. CV is an excellent metric as long as the mean is not close to 0.

      $$\text{CV} = \frac{\text{Standard Deviation}}{\text{Mean}}$$

    5. UniformityCV (%): This metric is derived from the Coefficient of Variation (CV) and is tailored for microscopy quality control, where users aim to capture highly uniform images. It assumes low variation (CV≪1) and provides an intuitive measure of uniformity expressed as a percentage. A perfectly uniform image, with CV = 0 results in a uniformity of 100%, while increasing variability lowers the value. A uniformity of 0% corresponds to CV = 1, where the standard deviation equals the mean intensity, indicating significant intensity variation. This metric is particularly useful in controlled imaging conditions typical of microscopy quality control. It assumes low CV value. UniformityCV offers a simple robust and user-friendly way to assess image uniformity. 

      $$\text{Uniformity}_{CV} = (1 - \text{CV})$$
  2. Centering Accuracy (%): Assesses how close the brightest region is to the image center. Defined as:
    $$\text{Centering Accuracy} = 1 - \frac{2}{\sqrt{\text{Image Width}^2 + \text{Image Height}^2}} \times \sqrt{(\text{X}_{\text{Ref Pix}} - \frac{\text{Image Width}}{2})^2 + (\text{Y}_{\text{Ref Pix}} - \frac{\text{Image Height}}{2})^2}$$
  3. Field Illumination Index: Combine both UniformityCV and the Centering Accuracy in a single measure. A field Illuminatin index of 100% indicates a perfectly uniform and centered image.
    $$\text{Field Illumination Index} = \text{Weigth}\times \text{Uniformity}_{CV} + (1 - \text{Weight})\times \text{Centering Accuracy}$$

QC Scope Field Uniformity Metrics (in bold the variables included in Essential Data)

Key OrderField NameData ExampleData TypeDescription
1Filename10x_Quad_Exp-01.cziStringName of the processed image
2Channel Nb4IntegerNumber of the Channel from 1 to n
3Channel NameDAPIStringName of the Channel
4Channel Wavelength EM (nm)465IntegerChannel Emission Wavelength
5Objective Magnification10xStringObjective Magnification
6Objective NA0.25FloatObjective Numerical Aperture
7Objective Immersion MediaAirStringObjective Immerion Media
8Gaussian Blur AppliedTRUEBooleanIf Gaussian Blur was applied
9Gaussian Sigma10IntegerSigma of the Gaussian Blur
10Binning MethodIso-DensityStringBinning Method used
11Batch ModeTRUEBooleanBoolean key to process images in batch mode (no Dialog)
12Save Individual FilesFALSEBooleanBoolean key to save individual files (1 csv data per file with 1 row per channel, 1 tif binned image par channel)
13Prolix ModeFALSEBooleanBoolean key display detailed plugin actions in the log
14Image Min Intensity856IntegerRaw Image Minimum of Pixel Intensities
15Image Max Intensity1080IntegerRaw Image Maximum of Pixel Intensities
16Image Mean Intensity959.1FloatRaw Image Mean of Pixel Intensities
17Image Standard Deviation Intensity24.3FloatRaw Image Standard Deviation of Pixel Intensities
18Image Median Intensity959IntegerRaw Image Median Pixel Intensity
19Image Mode Intensity110IntegerRaw Image Mode Pixel Intensity
20Image Width (pixels)1388IntegerImage Width in pixels
21Image Height (pixels)1040IntegerImage Height in pixels
22Image Bit Depth16IntegerImage Bit Depth
23Pixel Width (um)0.645FloatImage pixel width (unit/px)
24Pixel Height (um)0.645FloatImage pixel height (unit/px)
25Pixel Depth (um)1FloatImage voxel depth (unit/voxel)
26Space UnitmicronStringRaw Image Space Unit
27Space Unit StandardumStringStandardize Space Unit (nm, um, cm, m)
28Calibration StatusTRUEBooleanBoolean key displaying the calibration status
29Standard Deviation (GV)24.3FloatRaw Image Standard Deviation of Pixel Intensities
30Uniformity Standard (%)0.793FloatUniformity as calculated by MetroloJ_QC. Uniformity_Standard = (Min / Max)
31Uniformity Percentile (%)0.958FloatUniformity calculated with the average of the 5% and 95% pixel intensities.
Uniformity_Percentile = (1 - (Avg_Intensity95 - Avg_Intensity5) / (Avg_Intensity95 + Avg_Intensity5) )
32Coefficient of Variation0.0253FloatCoefficient of variation. CV = (Std_Dev / Mean)
33Uniformity CV based0.975FloatUniformity calculated from the Coefficient of variation. Uniformity_CV = (1 - CV) 
34X Center (pixels)694IntegerCoordinate in pixel of the center of the Image (Ideal centering). Image Width (pixels) / 2
35Y Center (pixels)520IntegerCoordinate in pixel of the center of the Image (Ideal centering). Image Height (pixels) / 2
36X Ref (pixels)230.4FloatCoordinate in pixels of the centroid of the largest particule identified in the last bin. Used to caculate the Centering Accuracy
37Y Ref (pixels)876.4FloatCoordinate in pixels of the centroid of the largest particule identified in the last bin. Used to caculate the Centering Accuracy
38X Ref (um)148.6FloatCoordinate in scaled unit of the centroid of the largest particule identified in the last bin.
39Y Ref (um)565.3FloatCoordinate in scaled unit of the centroid of the largest particule identified in the last bin.
40Centering Accuracy (%)0.32FloatCentering Accuracy = 1 - (2 / sqrt(Image Width**2 + Image Height**2)) * sqrt ( (X_Ref_Pix - Image Width/2)**2 + (Y_Ref_Pix - Image Height/2)**2)
41
Field Illumination Index (%)0.884
Float
Field Illumination Index  = Weight * UniformityCV+ (1 - Weight) * Centering Accuracy
Weight = 0.5

Key Metrics

  1. UniformityCV (%): 100% perfectly uniform. 0% or less if the Standard Deviation of pixel intensities in the image is equal or higher than the mean.
  2. Centering Accuracy (%): 100% illumination is perfectly centered on the image. Ratio of the distance of the centroid of the Indicates how the 10% brightest pixels to the center image 
  3. Field Illumination Index: Combine both UniformityCV and Centering Accuracy in a single Index. 100% indicates a perfectly uniform and centered image.

Results

  • Convert the Field Uniformity_Essential-Data_Merged.csv created by QC Scope Field Uniformity function into a .xlsx
  • Summarize the data with a pivot table
  • Use the provided spreadsheet template Field Uniformity_Template.xlsx
  • Enter your measurement into the highlighted cells of the template to visualize your results. The cells in grey are automatically computed.
  • Plot the Field illumination Index for each objective and filter combination

The 2x, 20x and 63x objectives have a field illumination index above 70% for all filters indicating an acceptable uniformity and centering accuracy. The 10x objective field illumination index is below 70% indicating a poor uniformity and/or Centering accuracy requiring further investigations.

  • Plot the Uniformity and Centering Accuracy for each objective and filter combination

All objectives show a good Uniformity. The 2x, 10x and 20x objectives have a centering accuracy below 70% indicating a poor illumination centering.

Iso-density map showing the localization of the centroid of the highest intensity bin for 10x and 63x objectives.

Field illumination Index for each objective and filter combination

Conclusion

Centering accuracy could be improved on the 2x and 10x objectives. This is not too much of a concern since Uniformity is well above 70%. 


Channel Alignment

Usage

  1. Open FIJI.
  2. Launch the QC Scope Toolbar by navigating to Plugins>QC Scope>QC Scope Toolbar.
  3. Click on Ch Alignment.
    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)
  4. QC Scope will try to read the Metadata from the first image and pre-process all the channels with the default or the last used processing settings
  5. It will display the metadata, the initial results and the processing options in a dialog
  6. Check the metadata and the results. If it looks good you can click OK. You can also modify the the metadata and processing options

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

    1. At least 2 CSV files are saved :

      1. Channel-Alignment_All-Data_Merged.csv gathers all the measured parameters
        Channel Alignment_All-Data_Merged.csv

      2. Channel Alignment_Essential-Data_Merged.csv gathers only the essential information
        Channel Alignment_Essential-Data_Merged.csv

    2. Optionally, if Save Individual Files is selected QC Scope will also save:
      1. 1 CSV file per image gathering all the measured parameters for each channel pair (Image-Name_Channel-Alignment_All-Data.csv)

Settings

  • Microscope Settings: Read from the image metadata or from the preferences: Objective Magnification (character), NA (Numeric>0), and Immersion media 
  • Image Settings: Read from the image Calibration. Pixel Width (Numeric>0), Height (Numeric>0), Depth (Voxel) (Numeric>0), Unit (character). QC Scope uses standard space unit (nm, um, mm, cm, m, in, pixels) and will try to convert the entered value into one of those.
  • Channel Settings: Read from the image metadata or from the preferences, for each channel: Name (character) and Emission Wavelength in nm ((Numeric>0)) as well as displaying the source of the values
  • Processing Settings:
    • Detection Method:
      • Log Detector: Laplacian of Gaussian (LoG) detector. From Trackmate: The LoG detector is the best detector for Gaussian-like particles in the presence of noise. It is based on applying a LoG filter on the image and looking for local maxima. The Laplacian of Gaussian result is obtained by summing the second order spatial derivatives of the gaussian- filtered image, and normalizing for scale. Reference: Trackmate manual (page 52). 
      • Dog Detector: Difference of Gaussian (DoG) detector. From Trackmate: This detector is based on the Difference of Gaussian (DoG) filter. It approximates the Laplacian of Gaussian (LoG) filter with the aim at offering better speed. It is commonly used when applying a collection of DoG filters tuned to a wide range of scales. Reference: Trackmate manual (page 52). 
    • Threshold: This is a quality threshold. Only spots above the quality threshold will be detected. The quality value is larger for : Bright spots, spots which diameter is close to the specified diameter.
    • Diameter: This is the diameter for the detection of spots with the indicated unit. Usually this is the diameter of the beads used for the channel alignment.
    • Median Filtering: If activated QC Scope will ask Trackmate to use a Median Filtering. Median filtering: will apply a 3 x 3 median filter prior to any processing.
      This can help dealing with images that have a marked salt and pepper noise which generates spurious spots. Reference: Trackmate manual (page 11). 
    • 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. Selecting an another channel will automatically enable Test Processing.
    • Batch Mode: If activated, QC Scope will re-use the settings without displaying the dialog unless metadata differs or the detection fails.
    • Save Individual Files: If activated, QC Scope will save an additional CSV File per image named Image-Name_Channel-Alignment_All-Data.csv gathering all the measured parameters for each channel pair (1 row per channel pair = Nb Channel2 rows per file. 
    • Prolix Mode: Display all the QC Scope actions in the log. If used in combination with Save Individual Files, it will save the original Trackmate spot table (1 per channel)
    • Subpixel Precision: If activated QC Scope will ask Trackmate to use a subpixel localization for the detection of spots

    • Test Processing: When selected the QC Scope Dialog will keep appearing. This is useful to test the Processing Settings. When you are satisfied you can uncheck Test processing to proceed to the next image. Changing the selected channel automatically select the Test Processing option.

  • Pre-detection results:
    • Nb of Detected spots: Indicate the number of detected spot per channel. To proceed, exactly one spot must be detected for every channel.
    • Max Quality: Indicate the maximum quality of all detected spots for each channel. The maximum quality can then be used to adjust the threshold value

Metrics

Channel Alignment measures how a single bead appears in different channels. QC Scope Channel Alignment detects one spot per channel and retrieve the xyz coordinates using TrackMate plugin More info about TrackMate. It then computes the distance between two spots and compare it to a reference spot. The position of the reference spot depends on the actual xyz resolution of the system. A Co-localization ratio is then calculated:

$$\text{Colocalisation Ratio} = \frac{\text{Distance}_{\text{Spot Ch1-Spot Ch2}}}{\text{Distance}_{\text{Spot Ch1-Spot Reference}}}$$
  • A Colocalization Ratio above 1 indicates that the Spot detected in Channel 2 is further away from the spot detected in Channel 1 than the reference spot. In other words the spot in channel 2 is further away than the resolution of the system. This indicates that Channel Alignment is not good and corrections should be performed using the pixel shift table.
  • A Colocalization Ratio below 1 indicates that the spot detected in Channel 2 is closer from the spot detected in channel 1 than the reference spot. In other words the distance between the spots detected in channel 1 and 2 is smaller than the resolution of the system. This ratio indicates a good Channel Alignment.

QC Scope Channel Alignment Metrics (in bold the variables included in Essential Data)

Key OrderField NameData ExampleData TypeDescription
1Filename20x_Quad_Exp-01.cziStringName of the processed image
2Objective Magnification20xStringObjective Magnification
3Objective NA0.5FloatObjective Numerical Aperture
4Objective Immersion MediaAirStringObjective Immerion Media
5Immersion Media Refractive Index1.0003FloatObjective Immerion Media Refractive Index
6Detection MethodDog DetectorStringMethod for the detection Log Dectector or Dog Detector
7Spot Diameter (um)4FloatSpot Diameter used for the detection
8Threshold Value20FloatQuality threhsold value used for the detection
9Subpixel LocalizationTrueBooleanSubpixel Localization used for the detection
10Median FilteringFalseBooleanMedian Filtering used for the detection
11Batch ModeTrueBooleanBoolean key to process images in batch mode (no Dialog)
12Save Individual FilesTrueBooleanBoolean key to save individual files (1 csv data per file with 1 row per channel, 1 tif binned image par channel)
13Prolix ModeFalseBooleanBoolean key display detailed plugin actions in the log
14Image Width (pixels)100IntegerImage Width in pixels
15Image Height (pixels)100IntegerImage Height in pixels
16Image Bit Depth16IntegerImage Bit Depth
17Pixel Width (um/px)0.3225FloatImage pixel width (unit/px)
18Pixel Height (um/px)0.3225FloatImage pixel height (unit/px)
19Pixel Depth (um/px)1.24FloatImage voxel depth (unit/voxel)
20Space UnitmicronStringRaw Image Space Unit
21Space Unit StandardumStringStandardize Space Unit (nm, um, cm, m)
22 Time UnitsecStringTime Unit
23Calibration StatusTrueBooleanBoolean key displaying the calibration status
24Channel 11IntegerNumber of the Channel 1 from 1 to n
25Name Channel 1Cy5StringName of the Channel 1
26EM Wavelength Channel 1 (nm)673IntegerChannel 1 Emission Wavelength
27Nb Detected Spots Ch11IntegerNb of Detected Spots for Channel 1
28Spot ID Ch12055IntegerSpot ID for Channel 1
29Spot Quality Ch1132FloatSpot Quality for Channel 1
30X Ch1 (um)16.005FloatCoordinate of the center of the detected spot for Channel 1 along the X axis in the indicated unit
31Y Ch1 (um)16.311FloatCoordinate of the center of the detected spot for Channel 1 along the Y axis in the indicated unit
32Z Ch1 (um)35.171FloatCoordinate of the center of the detected spot for Channel 1 along the Z axis in the indicated unit
33T Ch1 (sec)0FloatTime of the detected spot for Channel 1 in the indicated unit
34Frame Ch10IntegerFrame of the detected spot for Channel 1
35Radius Ch1 (um)2FloatRadius of the detected spot for Channel 1 in the indicated unit
36Visibility Ch1TrueBooleanSpot visibility for Channel 1
37Channel 23IntegerNumber of the Channel 2 from 1 to n
38Name Channel 2GFPStringName of the Channel 2
39EM Wavelength Channel 2 (nm)509IntegerChannel 2 Emission Wavelength
40Nb Detected Spots Ch21IntegerNb of Detected Spots for Channel 2
41Spot ID Ch22075IntegerSpot ID for Channel 2
42Spot Quality Ch2132FloatSpot Quality for Channel 2
43X Ch2 (um)16.05FloatCoordinate of the center of the detected spot for Channel 2 along the X axis in the indicated unit
44Y Ch2 (um)16.243FloatCoordinate of the center of the detected spot for Channel 2 along the Y axis in the indicated unit
45Z Ch2 (um)35.718FloatCoordinate of the center of the detected spot for Channel 2 along the Z axis in the indicated unit
46T Ch2 (sec)0FloatTime of the detected spot for Channel 2 in the indicated unit
47Frame Ch20IntegerFrame of the detected spot for Channel 2
48Radius Ch22FloatRadius of the detected spot for Channel 2 in the indicated unit
49Visibility Ch2TrueBooleanSpot visibility for Channel 2
50Channel PairCy5 x GFPStringCombination of Channel 1 x Channel 2 Names
51X Shift (um)0.046FloatDifference between the coordinates of Channel 2 and Channel 1 along the X axis in the indicated unit
52Y Shift (um)-0.068FloatDifference between the coordinates of Channel 2 and Channel 1 along the Y axis in the indicated unit
53Z Shift (um)0.547FloatDifference between the coordinates of Channel 2 and Channel 1 along the Z axis in the indicated unit
54X Shift (pixels)0.1FloatDifference between the coordinates of Channel 2 and Channel 1 along the X axis in pixels
55Y Shift (pixels)-0.2FloatDifference between the coordinates of Channel 2 and Channel 1 along the Y axis in pixels
56Z Shift (pixels)0.4FloatDifference between the coordinates of Channel 2 and Channel 1 along the Z axis in pixels
57Distance Lateral (um)0.082FloatLateral distance between the spot detected in Channel 2 and Channel 1 in the indicated unit
58Distance Axial (um)0.547FloatAxial distance between the spot detected in Channel 2 and Channel 1 in the indicated unit
59Distance 3D (um)0.553Float3D distance between the spot detected in Channel 2 and Channel 1 in the indicated unit
60Conversion Factor1000FloatConversion factor to convert Emission Wavelength from nm to the same unit than the calibrated image
61EMWavelength Unit Ch1 (um)0.673FloatEmission Wavelength in the indicated unit for Channel 1
62EMWavelength Unit Ch2 (um)0.509FloatEmission Wavelength in the indicated unit for Channel 2
63Nyquist Pixel Size Lateral Ch1 (um)0.337FloatNyquist Lateral pixel Size for Channel 1 in the indicated unit. Formula : Nyquist_Pixel_Size_Lateral = EMWavelength_Unit / (4 * Objective_NA)
64Nyquist Pixel Size Axial Ch1 (um)2.513FloatNyquist pixel Axial Size for Channel 1 in the indicated unit. Formula : Nyquist_Pixel_Size_Axial = EMWavelength_Unit / (2 * Refractive_Index * (1-cos(Theta))) with Theta = asin(Objective_NA / float(Refractive_Index))
65Nyquist Ratio Lateral Ch11FloatNyquist Lateral Ratio for Channel 1 in the indicated unit. Formula : Nyquist_Ratio_Lateral = Pixel_Width / Nyquist_Pixel_Size_Lateral. A ratio above 1 indicate the Pixel Size does not meet the Nyquist sampling criteria (Pixel too big)
66Nyquist Ratio Axial Ch10.5FloatNyquist Axial Ratio for Channel 1 in the indicated unit. Formula : Nyquist_Ratio_Axial = Pixel_Depth / Nyquist_Pixel_Size_Axial. A ratio above 1 indicate the Pixel Depth does not meet the Nyquist sampling criteria (Z Stack steps too big)
67Nyquist Pixel Size Lateral Ch2 (um)0.255FloatNyquist pixel Size for Channel 1 in the indicated unit. Formula : Nyquist_Pixel_Size_Lateral = EMWavelength_Unit / (4 * Objective_NA)
68Nyquist Pixel Size Axial Ch2 (um)1.9FloatNyquist Lateral Ratio for Channel 2 in the indicated unit. Formula : Nyquist_Ratio_Lateral = Pixel_Width / Nyquist_Pixel_Size_Lateral. A ratio above 1 indicate the Pixel Size does not meet the Nyquist sampling criteria (Pixel too big)
69Nyquist Ratio Lateral Ch21.3FloatNyquist Axial Ratio for Channel 2 in the indicated unit. Formula : Nyquist_Ratio_Axial = Pixel_Depth / Nyquist_Pixel_Size_Axial. A ratio above 1 indicate the Pixel Depth does not meet the Nyquist sampling criteria (Z Stack steps too big)
70Nyquist Ratio Axial Ch20.7FloatNyquist pixel Size for Channel 2 in the indicated unit. Formula : Nyquist_Pixel_Size_Lateral = EMWavelength_Unit / (4 * Objective_NA)
71Resolution Lateral Theoretical Ch1 (um)0.686FloatTheoretical Lateral Resolution for Channel 1 in the indicated unit. Formula: Resolution_Lateral_Theoretical = (0.51 * EMWavelength_Unit) / (Objective_NA)
72Resolution Axial Theoretical Ch1 (um)4.766FloatTheoretical Axial Resolution for Channel 1 in the indicated unit. Formula: Resolution_Axial_Theoretical = (1.77 * Refractive_Index * EMWavelength_Unit) / (Objective_NA ** 2)
73Resolution Lateral Practical Ch1 (um)0.686FloatPractical Lateral Resolution for Channel 1 in the indicated unit. If the Nyquist Lateral Ratio is above 1 the Practical Lateral Resolution = Theoretical Lateral Resolution x Nyquist Lateral Ratio otherwise the Practical Lateral Resolution = Theoretical Lateral Resolution
74Resolution Axial Practical Ch1 (um)4.766FloatPractical Axial Resolution for Channel 1 in the indicated unit. If the Nyquist Axial Ratio is above 1 the Practical Axial Resolution = Theoretical Axial Resolution x Nyquist Axial Ratio otherwise the Practical Axial Resolution = Theoretical Axial Resolution
75Resolution Lateral Theoretical Ch2 (um)0.519FloatTheoretical Lateral Resolution for Channel 2 in the indicated unit. Formula: Resolution_Lateral_Theoretical = (0.51 * EMWavelength_Unit) / (Objective_NA)
76Resolution Axial Theoretical Ch2 (um)3.605FloatTheoretical Axial Resolution for Channel 2 in the indicated unit. Formula: Resolution_Axial_Theoretical = (1.77 * Refractive_Index * EMWavelength_Unit) / (Objective_NA ** 2)
77Resolution Lateral Practical Ch2 (um)0.658FloatPractical Lateral Resolution for Channel 2 in the indicated unit. If the Nyquist Lateral Ratio is above 1 the Practical Lateral Resolution = Theoretical Lateral Resolution x Nyquist Lateral Ratio otherwise the Practical Lateral Resolution = Theoretical Lateral Resolution
78Resolution Axial Practical Ch2 (um)3.605FloatPractical Axial Resolution for Channel 2 in the indicated unit. If the Nyquist Axial Ratio is above 1 the Practical Axial Resolution = Theoretical Axial Resolution x Nyquist Axial Ratio otherwise the Practical Axial Resolution = Theoretical Axial Resolution
79X Ref (um)16.143FloatCoordinate in indicated unit of the reference spot in the along the X axis. The reference spot is a calculated as a spot at the interesect between the Line defined by Spot Channel 1 and Spot Channel 2 coordinates and an ellipse centered on Spot Channel 1 with Distance Lateral Ref as a semi-minor axis and Distance Axial Ref as a semi-major axis
80Y Ref (um)16.106FloatCoordinate in indicated unit of the reference spot in the along the Y axis. The reference spot is a calculated as a spot at the interesect between the Line defined by Spot Channel 1 and Spot Channel 2 coordinates and an ellipse centered on Spot Channel 1 with Distance Lateral Ref as a semi-minor axis and Distance Axial Ref as a semi-major axis
81Z Ref (um)36.825FloatCoordinate in indicated unit of the reference spot in the along the Z axis. The reference spot is a calculated as a spot at the interesect between the Line defined by Spot Channel 1 and Spot Channel 2 coordinates and an ellipse centered on Spot Channel 1 with Distance Lateral Ref as a semi-minor axis and Distance Axial Ref as a semi-major axis
82X Ref Shift (um)0.138FloatRelative distance in the indicated unit between the reference spot and the spot detected in Channel 1 along the X axis
83Y Ref Shift (um)-0.205FloatRelative distance in the indicated unit between the reference spot and the spot detected in Channel 1 along the Y axis
84Z Ref Shift (um)1.654FloatRelative distance in the indicated unit between the reference spot and the spot detected in Channel 1 along the Z axis
85Semi Minor Axis (um)0.343FloatThis is the semi minor axis of an ellipse defining the maximum distance in the XY plan calculated by dividing the largest Practical Lateral Resolution by 2.
86Semi Major Axis (um)2.383FloatThis is the semi major axis of an ellipse defining the maximum distance in the Z plan calculated by dividing the largest Practical Axial Resolution by 2.
87Distance Lateral Ref (um)0.247FloatDistance between the reference spot and the spot detected in Channel 1 in the XY plan in the indicated unit
88Distance Axial Ref (um)1.654FloatDistance between the reference spot and the spot detected in Channel 1 in the Z plan in the indicated unit
89Distance 3D Ref (um)1.673FloatDistance between the reference spot and the spot detected in Channel 1 in the 3D in the indicated unit
90Colocalization Ratio0.3FloatRatio between the 3D Distance (Channel 1 Channel 2) and the 3D Reference Distance. A ratio above 1 indicates the spot detected in channel 2 is further than the pratical resolution of the system. Formula: Colocalization_Ratio = Distance_3D /Distance_3D_Ref

Key Metrics

  1. Colocalisation Ratio: A ratio above 1 indicates the distance between the spot detected in channel 1 and 2 is larger than the practical resolution of the system: Channel Alignment is not good and corrections should be performed using the pixel shift table.

Results

  • Convert the Channel Alignment_Essential-Data_Merged.csv created by QC Scope Channel Alignment function into a .xlsx
  • Summarize the data with a pivot table
  • Use the provided spreadsheet template Channel Alignment_Template.xlsx
  • Paste the Colocalization Ratio and the XYZ pixel shifts in the Shift Tab. The cells use conditional formatting to highlight cells with a ratio above 1.0.

These results indicates that the 63x objective requires correction for the DAPI channel. User should be informed to correct the images.

63x DAPI (Cyan) and Cy5 (Magenta) 4um bead raw image.


  63x DAPI (Cyan) and Cy5 (Magenta) 4um bead corrected for chromatic shift.

 

63x DAPI (Cyan) and Cy5 (Magenta) 4um bead  Z-Stack.

63x DAPI (Cyan) and Cy5 (Magenta) 4um bead Z-Stack corrected for chromatic shift.

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