I am running into issues when trying to analyze sets of data consisting of a bubble that decreases in size over time. Most of my issues are due to the poor lighting and contrast of the image, which has made thresholding very hard. I want to be able to threshold the bubble so that I can run it through a MATLAB code which measures the radius over time. I am working with tiff stacks with anywhere from 80-500 images per stack. My current methodology, which does not work well, is as follows:
- Adjust Brightness and Contrast
- Crop to region of interest
- Try “find edges” but almost never works
- Have tried converting to an 8-bit image, does not help at all
- Attempt color thresholding (almost never works)
- Open image in Trainable Weka Segmentation using FIJI
- Manually select “bubble” and “background” areas and let WEKA run
- Repeat WEKA as required
- Run tiff stack through a MATLAB code to calculate diameter for every image, giving me a plot of diameter change vs time
- I use the MATLAB code because “Analyze Particles” was not working well enough for me, but I believe that if I can get accurate thresholding using “Analyze Particles” would be ok
Example Raw Image:
My questions are:
WEKA usually is not robust enough to accurately threshold every image in my dataset. Sometimes it will work for part of the stack, but not all of it. I currently use the “difference of gaussians” and “sobel filter” training features on WEKA with all other default settings. Are there different settings I should use that would work better?
Should I be using WEKA for thresholding / segmentation? Is there anything else you would recommend that is better than WEKA?
Even when using WEKA with only two training features, analyzing one stack takes anywhere from 15-30 minutes. How can I make this faster? I tried increasing the memory and threads available to FIJI, but that did not help.