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theoretically yes, but I guess it is not relevant. Since we now use the tasklist feature. And before that, I used the described workaround. So this is not needed anymore.
Mar 24 2023
@gaoh is this still an open issue?
Dec 9 2022
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Nov 25 2022
Discussion result: nice to have wären auch die Informationen des "first pass" (-> welche reader configuratoin, findet wieviele volumes und welche Dateien werden verwendet) schön.
Oct 10 2022
Sep 21 2022
To make our live a bit easier. I would say it is a data problem ;).
oh so I forgot to send it: But this is, what my browser had cashed: "Yes, so I recently tested it, with the current release."
But also, if I remember correctly, this was due to the Phantom dataset we have as the default dataset:
I removed a few slices at the end, and now it is working.
@gaoh Ping
Sep 15 2022
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Jul 22 2022
ok, but then the GPU problem is also feasible! If it is for a pre-known time-limited usage, like in an interactive session, I don't see a problem assigning a GPU to the container.
In T29243#240152, @gaoh wrote:What is the advantage of running nnunet in MITK in kaapana, over directly running nnunet in kaapana?
If you have a bunch of data, then the airflow workflow is the way to go.
To point 1, in Kubernetes you can mount any path/volume to the desired mounting point. So I could just mount the directory in the MITK container in e.g. /models
Jul 18 2022
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May 17 2022
yes, that will help. Also, this worklist will be quite helpful, allowing a new form of "batch-processing".
May 16 2022
Yes, so I changed it already, and I am using the seriesUID as name for the images. Additionally, I had to add the layer property: Because by introducing the image name property, somehow the layer is also set (to a high number, probably). When I create a new SEG without setting the layer of the image to 0, the SEG is only put on top, when opening the data manager.
May 13 2022
@gaoh Would you be so kind and verify that the problem still exists? Thanks.
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Jan 27 2022
Since in the input image a required tag is missing, MITK cannot provide a fix, allowing a success in dcmqi
In T28886#232894, @kalali wrote:Please check if the problem persists now with T28903: [Segmentation] Monitoring of segmentation nodes in views is error prone/ not safe. merged into develop.
Jan 26 2022
Input data to reproduce the error:
We discussed in the meeting:
- Exception handling is a good idea and should be the way to handle it. So mitk has to throw the exception and not show a success.
- Since in the input image a required tag is missing, MITK cannot provide a fix, allowing a success in dcmqi