ImageJ

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ImageJ Data Processing

1. Open the image: File → Open


2. Set the image scale to nm:

        2a. Draw a line on the image’s already existing scale bar → Analyze →  
        2b. Set Scale → Fill out the scale window as desired (make sure to put 
        2c. the known distance and units)


3. Crop off the label part of the image to eliminate it from the image processing : Pick the region with the rectangle → Image → Crop


4. Filter out the small voids (smoothing agent): Process → Filters → Median (radius = 2 pixels)


5. Convert the image to 8-bit: Image → Type → 8-bit


6. Save the image before thresholding. Save it as tiff.


7. Open edited image: File → Open → Edited image


8. Thresholding: Image → Adjust → Autohreshold → Choose threshold model (Huang, Li etc.) → Apply. Here it is most important to be consistent with the model choice when comparing the results.

  • Note: Threshold option gives us a binary image, where 0 is true black and 225 is true white. In our case, black is usually a hole and white is a ligament.


9. If needed, use Watershed option to separate curvatures. This is useful for separating cells.


10. Save thresholded image as well. Save it as tiff.


11. Analyze the particles: Analyze → Analyze Particles (10nm - infinity) → Show → Outlines → Summarize → Clear Results → Display Results

  • Note: Summary is all related to black, pores.


12. One can use Macro plugin to write a macro code to run the analysis process over and over again. Macro can be done only on the same magnification images.


13. For the ligament processing it is better to use Tatiana’s Matlab Script.


14. Check the data.