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Bogdan Dzyubak


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17 Sep 2012 Intensity inhomogeneity correction LEMS method to correct for intensity inhomogeneity of MR images Author: Olivier Salvado

Seems to work well once tweaked. It won't run out-of-the-box, though.

1) Go to PolyMaskFilter.m and change if ~exist('basis') for if exist('basis') ~= 1. It's a matlab version issue.

2) After selecting the area to be cropped, you need to right click on the image and click crop. It's a little unintuitive.

3) You may need to hardcode or otherwise adapt parameter estimation, such as background std.

4) The 'manual threshold' option can only be use to give the low threshold.

After fixing these, it seems to give me a pretty good result, though I've yet to evaluate whether it will work on images universally.
Thanks for posting. Good luck to users.

08 Jun 2012 Peak Fitter Command-line peak fitter for time-series signals. Version 5.7, September, 2014 Author: Tom O'Haver

Using the Autozero function (default) tends to lead to zeros and Nan's being returned in some occasions. Commenting out the autozeroeing line fixed the problem but it would be nice to have it available.

30 Apr 2012 EM algorithm for Gaussian mixture model EM algorithm for Gaussian mixture. Works on arbitray dimensions with high speed and precision. Author: Mo Chen

Simple to use, fast, and doesn't crash.

02 Apr 2012 Animated GIF How to generate an animated GIF from MATLAB Author: Robert Bemis

If I use the attached GIF in powerpoint, it does play. If I rerun the code it yields a gif with a single frame. Are any additional inputs necessary?

05 Mar 2012 Peak Fitter Command-line peak fitter for time-series signals. Version 5.7, September, 2014 Author: Tom O'Haver

Hi, Tom
I'm finding this code very useful, although I was wondering if you could look into a couple more things. Some of these instabilities may be cause by the fact that I have a truncated peak that I zero padded (see above):

1. In some datasets, I get NaN's and 0's if I try to fit for example 4 peaks, but 3 works ok. In the latter case, I tend to get peaks positioned at something like -4e004, whereas my data range is 0 to 300. I haven’t been able to find a trend as to when this occurs.

2. When I run any fit other than Gaussian, I get NaN's and 0's for all peak parameters. [Results1,MeanFitError1,BestStart,xi,yi1]=peakfit([x1 y1],100,200,2,1); -- Is ok, but changing the "1" at the end causes issues.

3. If I let it choose Gaussian as a default, ( i.e. [Results1,MeanFitError1,BestStart,xi,yi1]=peakfit([x1 y1],100,200,2); ), it takes about 150 seconds to process my 300 data points. If I explicitly ask for a Gaussian shape (add a "1" as the last input), it takes seconds.
Looking forward to further updates,
Thanks for the work

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