First of all, thank you for making such a brilliant program. So far I’ve been working on making an ImageJ macro and this just blows all those attempts away.
My goal is to analyze images generated by our ScanScope FL scanner to get a count of GFP positive neurons. A scan has DAPI (blue), GFP (green) and an additional red channel I use for determining background fluorescence in the Red spectrum. A single Slide (preview jpg attached) has a resolution of about 100,000 x 40,000 pixels.
Compressed with JPEG2000 and embedded in an svs wrapper, each channel is thus about 1gb+ each. Ignoring the DAPI channel which is irrelevant for this use, it’s still about 2GB (compressed) per slide - therefore I realize it’s probably a pipe dream to process a whole slide at once. Each slide contains approx 12 sections, composed of 2 hemispheres - representing a single unit. Therefore ideally I would like to get the count of the # of positive cells in each hemisphere of each cell. I realize at this point that probably the only way to get this is to separate each hemisphere by hand - which is fine. Doing this manually and saving as TIF with LZW produces files about 50mb - which took CellAnalyzer about 20min to say it can’t load. Reducing the resolution to 25% of original (3kx5k) is still 25MB with LZW. However when I try to open this file with CellAnalyzer - it comes out rather garbled. I tried attaching a file that shows this but when i crop it down to 10MB the problem is no longer there -Here’s a link: yousendit.com/download/T1Vr … MUN4dnc9PQ (55MB)
Does cell Analyzer support tiled tif? I have so far only gotten good results on a small scale (1.2x1.2k) how high can I go and still have it work?
some details about the computer: interl core i7 process 2.66 Ghz, 8GB RAM. Tried both OS 10.6 and Windows 7.
If it matters; Programs like Photoshop, Preview, Photoviewer open the files in 1-2 seconds. Image J and imageanalyzer take ages - makes me think it’s a file compatibility issue rather than actual resource usage.
Any advice on how to proceed is much appreciated
(additionally, I have some questions about the optimal method of object id: currently I am subtracting the Red channel from the green channel, then using manual thresholding because none of the others give good result, but first I need the program to even load a decent size dataset)