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From: Helen K on 1 Jul 2010 21:37
"Valentin Rabanelly" <vjrabanelly(a)hotmail.com> wrote in message <i0gj20$esb$1(a)fred.mathworks.com>...
> Hey everyone!
>
> I'm trying to treat this image with Matlab :
> http://img710.imageshack.us/img710/3743/cerveau.jpg
> (original file for those who will try it in Matlab : http://www.mediafire.com/file/oj2wxtd2mnv/brains.pgm)
>
> Here are the instructions I have:
> The image shows a nuclear magnetic resonance of the brain. In this picture, the different tissue types have different levels of gray. Identify the regions of white matter in the histogram of the image.
>
> Use a combination of thresholds above and below the peak of white matter and simple arithmetic to create your own segmentation.
> Result expected:
> http://img808.imageshack.us/img808/2245/cerveauresultat.jpg
>
> Here is what I tried so far:
> "pictureAfterThreshold = brainPicture > 180;"
> Result:
> http://img338.imageshack.us/img338/6075/cerveauobtenu1.jpg
>
> This is very radical in the sense that it retains only the pixels whose value is between 180 and 255 in the original image. I liked the result a bit more nuanced, with a transition zone between the black and the white area in the result which is less steep.
>
> I also tested this:
> "grayLevels graythresh = (brainPicture);
> brainPictureBW im2bw = (brainPicture, grayLevels);"
> Result:
> http://img10.imageshack.us/img10/1740/cerveauobtenu2.png
>
> The result is similar to the one presented above, but in reality, a little further from the expected result because it filters too much the original image.
>
> Well, from here and with the instructions I have, I don't know which way to follow to achieve the expected result ... Could you please help me?
>
> Thank you very much!


Thanks you for the post.
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From: Christopher on 2 Jul 2010 00:44
It will be interesting to know what they mean by 'simple arithmetic'...

Presumably you are supposed to use the histogram of the original greyscale image to determine a suitable threshold. I'm not so sure if histogram equalisation is used as ImageAnalyst seems to be.

HE and CLAHE both tend to either make dark areas lighter or light areas darker - dependent on the position of the majority of the pixel values on the histogram. In contrast (pardon the pun..), the 'expected results' image that were provided (particularly the upper left result) seems to show some pixels becoming darker and other pixels becoming lighter??

Valentin, are you sure there's not some other material (i.e. formulas or steps) that have been suggested to you over the course of the lecture about image segmentation? It seems as if they are assuming you know a certain procedure or at least guidelines as to a recommended way to segment an image...

Chris
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