Comments on: Cell segmentation

By: Steve

Steve — Wed, 18 Mar 2009 13:01:38 +0000

Dexter—You might try using bwareaopen to remove the small “noise” objects detected.

By: deXter Holland

deXter Holland — Wed, 18 Mar 2009 12:22:32 +0000

http://img3.imageshack.us/my.php?image=sample01.jpg

hi all! i need to do cell detection on the image above (identify the presence of those ‘big’ cells). my main problem is the background (noise), i couldn’t remove them properly, so i couldn’t do the usual segmentation easily. for now i’m processing it on grayscale, based on the materials i’m reading.
any suggestion?

By: Steve

Steve — Mon, 09 Mar 2009 13:06:11 +0000

Francesco—It's your algorithm that doesn't recognize that there are many regions. It's hard to say for sure without looking at your image, but I'm not sure I understand why all your steps make sense. You might want to take a look at my News & Notes article about watershed-based segmentation.

By: Francesco

Francesco — Fri, 06 Mar 2009 15:06:14 +0000

I=imread(‘Open cells aluminium foam.tif’);
thresh=40;
BW=(I>40);
D=bwdist(I1,’euclidean’);
D1=imcomplement(D1);
H=imhmin(D1,13,6);
L=watershed(H);
d=imcomplement(BW)&L;
Now i have reconstructed my open cell foam but if i want to make a geometrical analysis it seems to be that the image has only one region instead of hundreds,because matlab doesn’t recognize that there are many regions.
How i can make to solve this problem??

By: Steve

Steve — Wed, 04 Mar 2009 12:28:45 +0000

Francesco—This blog post has some example code. You might also want to look at the watershed segmentation demo in the Image Processing Toolbox.

By: Francesco

Francesco — Wed, 04 Mar 2009 11:41:50 +0000

Goodmorning,
in my engineering degree study i have to make a microstructural characterization of open cell aluminium foams.
After i have done a watershed transform on my 2D slice i have to do a masking of the complement of the binary starting image and the watershed one to reduce the oversegmentation but i don’t know how to make this.

By: Pratyusha

Pratyusha — Thu, 12 Feb 2009 17:56:38 +0000

Thank you for letting me know. I will try to use a kalman filter for it, or color code the image to highlight the tumor areas.

By: Steve

Steve — Mon, 02 Feb 2009 18:11:39 +0000

Pratyusha—I don’t have any suggestions for you.

By: Pratyusha

Pratyusha — Sat, 31 Jan 2009 00:01:50 +0000

HI Steve,
I have a similar problem with segmentation of tumors in an Ultrasound image.
I use a .jpg image file and edge detection techniques, but most of the times it does not work, as the background of an US image is not that clear, i.e., there is a very smooth gradient. I could send/upload some of the files (Images) so you can have a look at them.
Please suggest a suitable edge detection technique for these kind of images.

Thank you!

By: Steve

Steve — Fri, 30 Jan 2009 12:14:59 +0000

Ragu—In my comment #105, I gave a link to my News & Notes article on the watershed transform, which explains the basic concepts of using the transform for segmentation. I encourage you to take a look at it. Here’s an important sentence: “The key behind using the watershed transform for segmentation is this: Change your image into another image whose catchment basins are the objects you want to identify.” Often, the original grayscale image does not have the property that its catchment basins correspond to the objects you are trying to segment. Markers, minima imposition, computing gradient magnitudes, etc., are all techniques for making that happen.