Equivalent of watershed for cutting connected components of an image of particles?

[Thomas Caswell]

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 <claiborne.morton at 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 <
> claiborne.morton at 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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