Closed rohanbanerjee closed 4 months ago
The list of 50 subjects chosen for manual corrections is below: qc_fail.yml.zip
The QC report for the segmentations manually corrected by me for the above 50 subjects is below: qc_round_3_corrected.zip
improper shape of the cord (look carefully at the boundaries when making manual correction):
underseg:
incorrect:
I'll stop doing the rest of the QC-- pls make sure this is correct before sending it to me
Here's what i did so far: qc_flags.json
Closing the issue since the round 3 training was successfully completed (including running inference and manual correction)
Continuation from the previous round of training: https://github.com/sct-pipeline/fmri-segmentation/issues/35
What is the round 3 model
The model which was fine-tuned on the manually corrected segmentations as per the QCs mentioned in #38 is the
round 3
model. A total of 40 images were added in the training of this model since we fine-tuned the previously trainedround 2
model.A list of subjects used for the
fine-tuning
is below: finetuning.ymlThe config (containing preprocessing, hyperparameters) for nnUNetv2 training is: plans.json
After the training was completed, I ran inference on the rest of the images whose segmentations have to be included in the consequent rounds of training (186 images), below is the QC. 50 subjects from these images will be chosen and included in the
round 4
of training:qc_round3_inference.zip
The steps to reproduce the above QC results (/run inference) are the following:
cd fmri-segmentation
Next steps:
held-out test set
(#33)