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TUM-CAMP-tutorials-contribution: DAF3D and Quicknat #1440
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Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
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View / edit / reply to this conversation on ReviewNB mingxin-zheng commented on 2023-06-28T07:15:46Z Thank you for the PR. According to our contributing guideline we would need a "Setup imports" instead of "Preprocess the data in folders" here. |
View / edit / reply to this conversation on ReviewNB mingxin-zheng commented on 2023-06-28T07:15:48Z Line #13. image_path_expression = "PROCESSED/MPRAGE/T88_111/OAS1_*_MR*_mpr_n*_anon_111_t88_masked_gfc.img" Is the path correct? It seems the runner is complaining about not finding the files:
IndexError Traceback (most recent call last)
For more details, this can be found in: TUM-CAMP-tutorials-contribution: DAF3D and Quicknat · Project-MONAI/tutorials@fd221ce (github.com) |
View / edit / reply to this conversation on ReviewNB mingxin-zheng commented on 2023-06-28T07:15:49Z Line #5. lossFunction = DiceCELoss(include_background=True, to_onehot_y=True, softmax=True) Please check the PEP 8 error regarding the variable naming:
TUM-CAMP-tutorials-contribution: DAF3D and Quicknat · Project-MONAI/tutorials@fd221ce (github.com)
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View / edit / reply to this conversation on ReviewNB mingxin-zheng commented on 2023-06-28T07:15:51Z Line #1. num_epochs = 20 We typically use |
Signed-off-by: Alexandra Marquardt <[email protected]>
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…into TUM-CAMP-tutorials
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Hi @vgonzalezd , As the module had been merged into MONAI core, could you please help update and complete this PR? Thanks in advance. |
Just a heads up, you can review notebook changes like this using GitNotebooks. e.g. this pull request https://gitnotebooks.com/Project-MONAI/tutorials/pull/1440 It allows inline comments on code and markdown, and it's free for public repos so I thought I'd share.. |
Fixes # .
Description
@Al3xand1a and @ge96lip create these 2 tutorials for 2 networks that were recently accepted in MONAI core:
DAF3D[1] and Quicknat[2]
We would like to have your feedback to improve the contribution. Thank you in advance!
For any questions send us an email to [email protected]
[1]DAF3D:
Wang, Y., Dou, H., Hu, X., Zhu, L., Yang, X., Xu, M., ... & Ni, D. (2019). Deep attentive features for prostate segmentation in 3D transrectal ultrasound. IEEE transactions on medical imaging, 38(12), 2768-2778.
https://github.com/wulalago/DAF3D/blob/master/README.md
[2]QuickNAT:
Roy, A. G., Conjeti, S., Navab, N., Wachinger, C., & Alzheimer's Disease Neuroimaging Initiative. (2019). QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy. NeuroImage, 186, 713-727.
https://www.sciencedirect.com/science/article/abs/pii/S1053811918321232
Checks
./figure
folder./runner.sh -t <path to .ipynb file>