Hi Mr_Skony,
I did it once by timing the taking of the pictures with the heartbeat of the patient.
The cycle of the heatbeat is subdivided into a diastolic and systolic phase.
If you take one picture at the diastolic and another picture at the systolic phase,
(and you get your patient to sit still and hold his breath for a second or two)
the only thing that has changed are the bloodvessels. Subtracting the two images
should in principle give you the bloodvessels (maybe some postprocessing will be necessary)
Kind regards
Angelika Erhardt
Gesendet: Donnerstag, 24. Juli 2014 um 13:56 Uhr
Von: "Dionysios Lefkaditis" <
[hidden email]>
An:
[hidden email],
[hidden email]
Betreff: Re: Retina vessel segmentation
Hello Mr_Skony,
It sounds like you might benefit from a machine learning approach to
perform the required segmentation. I suggest that you should give
Advanced Weka Segmentation plugin a try:
http://fiji.sc/wiki/index.php/Advanced_Weka_Segmentationcheers,
Dionysios
On Thu 24 Jul 2014 09:34:54 AM CEST, Burri Olivier wrote:
> Hi Mr_Skony,
>
> It would make sense that no threshold methods works, as some vessels seem bright, and others dark. Similarily, the illumination is very uneven, so I highly doubt any kind of automatic segmentation would work in this case. How are these images acquired?
>
> Also, perhaps you could provide a hand-drawn rendition of the structure you hope to extract as I am not sure what I am looking at and am by no means a rodent retina blood vessel expert :)
>
> Best
>
> Oli
>
> --
> ImageJ mailing list:
http://imagej.nih.gov/ij/list.html[
http://imagej.nih.gov/ij/list.html]
--
ImageJ mailing list:
http://imagej.nih.gov/ij/list.html[
http://imagej.nih.gov/ij/list.html]
--
ImageJ mailing list:
http://imagej.nih.gov/ij/list.html
Locked
