Re: Equivalent of watershed for cutting connected components of an image of particles?
Thomas, Unfortunately, the cells of interest are the sickle cells, so isolating cells on their side and sickle cells is really important. If anything, it would be better to toss out the healthy cells. When you say the "segmentation has gone sideways", what do you mean exactly? Juan, What would binary closing do in particular? I didn't understand what you were saying On Wednesday, March 11, 2015 at 7:01:54 PM UTC-4, Thomas Caswell wrote:
Jumping in from the peanut gallery, can you reliable identify when the segmentation has gone sideways? Looking at the second moment, area to bounding box area, or some other compactness measure?
If you can get away with it, you could just drop the offending cells. If not, then you can try eroding the joined cells until they split into multiple segments.
Tom
On Wed, Mar 11, 2015, 17:15 Claiborne Morton <claiborn...@gmail.com <javascript:>> wrote:
Hey thanks for the help, here are a few other issues we are running into. When a sickle cell is in contact with a regular cell, we cannot find a way to separate the two. Also bottom-middle circle is of a healthy blood cell that is on its side. The watershed function tends to break these cells into two or more partitions when the should not be separated. Any idea on how to fix these problems?
On Tue, Mar 10, 2015 at 2:12 PM, Claiborne Morton <claiborn...@gmail.com <javascript:>> wrote:
Hey guys, Im following up on Adam's behalf, but this is an example of an image we are working with in trying to separate cells that are touching each other. Also you can see the top middle particle has a crescent shape, but is actually a healthy red blood cell that has been segmented incorrectly because of glare. Is that a way to connect the two tips of the shape so that I could then run "binary_fill_holes()" to correctly segment the cell. Thanks!
On Wednesday, February 18, 2015 at 7:04:10 PM UTC-5, Adam Hughes wrote:
Hi,
In ImageJ, one can select watershedding to break up connected regions of particles. Are there any examples of using watershed in this capacity in scikit image? All of the examples I see seem to use watershedding to do segmentation, not to break connected particles in an already-segmented black and white image.
Also, is there a straightforward way to remove particles on a the edge of an image? Sorry, googling is failing me, but I know this is possible.
Thanks
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By 'sideways' I mean "didn't work right". On Thu, Mar 12, 2015 at 1:09 PM Adam Hughes <hughesadam87@gmail.com> wrote:
Thomas,
Unfortunately, the cells of interest are the sickle cells, so isolating cells on their side and sickle cells is really important. If anything, it would be better to toss out the healthy cells. When you say the "segmentation has gone sideways", what do you mean exactly?
Juan,
What would binary closing do in particular? I didn't understand what you were saying
On Wednesday, March 11, 2015 at 7:01:54 PM UTC-4, Thomas Caswell wrote:
Jumping in from the peanut gallery, can you reliable identify when the segmentation has gone sideways? Looking at the second moment, area to bounding box area, or some other compactness measure?
If you can get away with it, you could just drop the offending cells. If not, then you can try eroding the joined cells until they split into multiple segments.
Tom
On Wed, Mar 11, 2015, 17:15 Claiborne Morton <claiborn...@gmail.com> wrote:
Hey thanks for the help, here are a few other issues we are running into.
When a sickle cell is in contact with a regular cell, we cannot find a way to separate the two. Also bottom-middle circle is of a healthy blood cell that is on its side. The watershed function tends to break these cells into two or more partitions when the should not be separated. Any idea on how to fix these problems?
On Tue, Mar 10, 2015 at 2:12 PM, Claiborne Morton <claiborn...@gmail.com
wrote:
Hey guys, Im following up on Adam's behalf, but this is an example of an image we are working with in trying to separate cells that are touching each other. Also you can see the top middle particle has a crescent shape, but is actually a healthy red blood cell that has been segmented incorrectly because of glare. Is that a way to connect the two tips of the shape so that I could then run "binary_fill_holes()" to correctly segment the cell. Thanks!
On Wednesday, February 18, 2015 at 7:04:10 PM UTC-5, Adam Hughes wrote:
Hi,
In ImageJ, one can select watershedding to break up connected regions of particles. Are there any examples of using watershed in this capacity in scikit image? All of the examples I see seem to use watershedding to do segmentation, not to break connected particles in an already-segmented black and white image.
Also, is there a straightforward way to remove particles on a the edge of an image? Sorry, googling is failing me, but I know this is possible.
Thanks
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Hey Adam, "Closing" is a dilation followed by an erosion. If you have "gaps" that are smaller than the footprint (aka structuring element) of the operation, they will be "closed". =) (e.g. a C turning into an O if the distance between the tips of the C is small enough.) See a small example here: http://nbviewer.ipython.org/github/jni/skimage-tutorials/blob/master/scipy-2... Though come to think of it we should change the shape to be a C rather than an O with a thin bit. Juan. On Fri, Mar 13, 2015 at 4:09 AM, Adam Hughes <hughesadam87@gmail.com> wrote:
Thomas, Unfortunately, the cells of interest are the sickle cells, so isolating cells on their side and sickle cells is really important. If anything, it would be better to toss out the healthy cells. When you say the "segmentation has gone sideways", what do you mean exactly? Juan, What would binary closing do in particular? I didn't understand what you were saying On Wednesday, March 11, 2015 at 7:01:54 PM UTC-4, Thomas Caswell wrote:
Jumping in from the peanut gallery, can you reliable identify when the segmentation has gone sideways? Looking at the second moment, area to bounding box area, or some other compactness measure?
If you can get away with it, you could just drop the offending cells. If not, then you can try eroding the joined cells until they split into multiple segments.
Tom
On Wed, Mar 11, 2015, 17:15 Claiborne Morton <claiborn...@gmail.com <javascript:>> wrote:
Hey thanks for the help, here are a few other issues we are running into. When a sickle cell is in contact with a regular cell, we cannot find a way to separate the two. Also bottom-middle circle is of a healthy blood cell that is on its side. The watershed function tends to break these cells into two or more partitions when the should not be separated. Any idea on how to fix these problems?
On Tue, Mar 10, 2015 at 2:12 PM, Claiborne Morton <claiborn...@gmail.com <javascript:>> wrote:
Hey guys, Im following up on Adam's behalf, but this is an example of an image we are working with in trying to separate cells that are touching each other. Also you can see the top middle particle has a crescent shape, but is actually a healthy red blood cell that has been segmented incorrectly because of glare. Is that a way to connect the two tips of the shape so that I could then run "binary_fill_holes()" to correctly segment the cell. Thanks!
On Wednesday, February 18, 2015 at 7:04:10 PM UTC-5, Adam Hughes wrote:
Hi,
In ImageJ, one can select watershedding to break up connected regions of particles. Are there any examples of using watershed in this capacity in scikit image? All of the examples I see seem to use watershedding to do segmentation, not to break connected particles in an already-segmented black and white image.
Also, is there a straightforward way to remove particles on a the edge of an image? Sorry, googling is failing me, but I know this is possible.
Thanks
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participants (3)
-
Adam Hughes -
Juan Nunez-Iglesias -
Thomas Caswell