SSL4MIS
SSL4MIS copied to clipboard
HiLab-git
Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
Hi, Good work and thanks for the scripts, it's good to use. I've trained a URPC model on brats2019 dataset by using this script in `train_brats2019_semi_seg.sh` : `python -u train_uncertainty_rectified_pyramid_consistency_3D.py...
Hello, I would like to know how many experiments the mean and standard deviation of the experimental results in the article are obtained after？
Hi,I have a confusion hope can be helped， In semi-supervised segmentation, why the performance improvement always becomes smaller as the amount of labeled data increases?  Thanks!
Thanks for your wonderful work. I have learned a lot from it. I'm a little confused about the calculation of the metrics (e.g., Dice, ASD) in test_3D_utils on line 106...
Hello, I find that when I use nibabel to read a picture as numpy, numpy will rotate 90 degrees, but when I finally save numpy as nibabel, the picture direction...
Hello, when I changed batchsz=4, labelde_batchsz=2, the val set accuracy improved a lot, I don't know the reason
I am wondering why the val set dice of the last few epochs is not the best, but usually the val set accuracy in the middle of training is the...
The python environment I am using is 3.9. when i run train_mean_teacher_3D, the following error occurred, does anyone know where is the problem? Namespace(root_path='../data/BraTS2019', exp='BraTs2019_Mean_Teacher', model='unet_3D', max_iterations=30000, batch_size=4, deterministic=1, base_lr=0.01,...
Exciting work! But how can I use it to train our own dataset, I didn't find the data preprocessing documentation
