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Subject: Re: Horn Detection in Leukaemia Images
Date: Wed, 18 Feb 2009 06:56:02 +0000 (UTC)
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If you happen to know Java pretty well and are willing to commit to the more manual option, you could check out ImageJ - which is freely available, making it easier to share your work.  I've written ImageJ plugins to do a few semi-automated tasks - I prefer it to MATLAB for making nice user interfaces when the user will have to click a lot, but it is much, much easier and faster to design and test out more complicated new algorithms in MATLAB.  In any case, there are lots of ImageJ plugins available for download on the website - they might at least give you some inspiration.

Unless I really preferred Java programming to MATLAB though, I'd probably stick with the latter because the fiddly and annoying problems of automated detection are usually more interesting than the fiddly and annoying problems of user interface design.  If you have time, you can make a MATLAB user interface in GUIDE - if not, you can use functions like uigetfile to make things a bit easier for the user at the command line.

The functions getpts from the Image Processing Toolbox can be used to, well, get points.  I guess you could prompt the user three times: once to click on normal cells, once to click on cells with horns, once to click on horns (assuming an average number of horns per cell is ok).  You can overlay markers on the image using the line or plot functions.

getline would allow the user to draw around a cell instead.

The results on your detection images look pretty good, although I wonder how the other image would fare.  My images (also cells, but different ones) haven't contained interesting features that are consistently enough shaped for me to rely on the Hough transform, but I didn't explore it for very long and maybe it is more powerful than I realise.

Maybe Image Analyst, or anyone else, has better segmentation suggestions.  I briefly tested a couple of techniques I knew on your images, with the familiar result that they seem to almost worked well.... but, frustratingly, not quite well enough, because some of the borders between cells are quite indistinct.