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Lumbar rootlets - first model training #48
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Dataset203_LumbarRootletsTrying a binary model trained on both cervical (n=31) and lumbar (n=6) rootlets:
nnUNetv2_plan_and_preprocess -d 203 --verify_dataset_integrity -c 3d_fullres
CUDA_VISIBLE_DEVICES=2 nnUNetv2_train 203 3d_fullres 0 # I do not use `-tr` --> 1000 epochs in default |
Observations so far: Legend:
Next step: try transfer learning, i.e., pre-train on cervical, finetune on lumbar |
@valosekj how different are the labels performed by Raphaelle and that performed by Theo/you? If too different, the model will get confused. |
Cervical and lumbar labels differ a lot. Lumbar rootlets have much greater angulation and thus a greater overlap between levels.
Indeed, this was my concern and why I tried the lumbar model only. |
aouch! that is a tricky project indeed 😅 |
Dataset201_LumbarRootlets and Dataset202_LumbarRootlets
This issue summarizes the training of the first models (
Dataset201_LumbarRootlets
- semantic,Dataset202_LumbarRootlets
- binary) for lumbar dorsal rootlets.Steps
(recoding using recode_nii.py)
Dataset201_LumbarRootlets
fold1
, 4 training and 2 validation images.dataset.json
1
) modelDataset202_LumbarRootlets
fold1
, 4 training and 2 validation images.dataset.json
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