Results on nnU-Net trained over 45 subjects mixing healthy and mild compression subjects

[abelsalm]

Here is a review on the last training I did on ann nnU-Net for spinal canal segmentation. I added more data using the previous training, 10th issue, trained the model on 45 subjetcs using the results of the inference, mixing data from spinge-generic, dcm-oklahoma, dcm-brno, sci-paris, and dcm zurich.

I trained the model for 400 epochs, with the randomly generated fold done by nnUNettrainer function.

So there were 5 subjetcs for the testing part, one from each dataset, and 40 for the training, I used the first fold, in this json file : splits_final.json

Here are the details of the training :

May be I could updload the qc report, anyway I already did more active learning and trained a new model on more data again, see in the next issue.

[abelsalm]

@jcohenadad @sandrinebedard @valosekj May be you think I should add things on this issue ? Anyway I'm opening an other one for the training I finished last week on 97 subjects.

[sandrinebedard]

You can also maybe specify that spinge-generic, the data is derivatives/data_preprocessed, and the versions of each dataset

[abelsalm]

Here is the QC for this session : https://drive.google.com/file/d/1-LQyUpK4OCnyP2akaeJCiM7Dyeq1acwO/view?usp=drive_link

[jcohenadad]

cool! some issues, notably:

• sub-3194B_ses-3194B_T2w_000_0000.nii.gz
• sub-3249B_ses-3249B_T2w_000_0000.nii.gz

but overall it looks ok

[abelsalm]

cool! some issues, notably:

• sub-3194B_ses-3194B_T2w_000_0000.nii.gz You mean on the superior part ? cause I don't see anything else ?