I want to quantify red spots (in situ hybridization signal) and count the purple nuclei. I will have 12 samples and several images per sample. I can optimize images better. So far I have saved this positive control image as a tiff. I think I defined the red spots fairly well with the following method. Please advise if you have other suggestions. I am wondering how to (1) apply the classifier I created in the Trainable Weka Segmentation tool to other images. (2) count nuclei on same images (3) write a macro to automate. I am a new ImageJ user, so any suggestions are appreciated. I’ll upload the original image (PPIB 40x), the background subtracted image and a thresholded image.
After watching a Fiji training video, I tried the following:
Import Image using Bio-formats. Select Grayscale & split channels.
Apply Gaussian Blur to Background image with Sigma 150
Use Image Calculator to subtract Background from Original image
Image 1 Original; Operation Subtract; Image 2 Background
Check the “Create New Window” and “32-bit (float) result
Rename Original - Bkgd; and Duplicate it.
Process > Enhance Contrast > Default is saturated pixels: 0.3% > OK
Plugins > Segmentation> Trainable Weka Segmentation
Zoom in using the “+” key
Create New Class
Settings > Name Class 1 “Spots” > Name Class 2 nuclei > Name Class 3 Background
Using line tool, draw across about 3 or 4 spots > Add to Spots
Then draw across about 3 or 4 cells > Add to Nuclei
Then hit “Train classifier”. This takes a minute or so.
Re-adjust and re-train if necessary until you think the spots, nuclei and background are properly defined. Use the “Toggle overlay” button to check how the program did at labeling.
Create Result. Duplicate
Image > Type > 8 Bit
Image > Adjust > Threshold > Default > Red > Apply
Process > Binary > Watershed
Analyze > Analyze Particles > Size (micron squared) 1000000-Infinity > Display results > > Clear Results > summarize > Exclude on edges
Thank you, Diane