This is the code for my graduation thesis and the solution for my BRATS 2020 Challenge.
Here are the four modes of the image and its mask
First,the image is cropped into patches.Runsrc/partition.py
,change the storage address of training set, verification set and test set successively.
train_brats_path = "your-Path_to/MICCAI_BraTS_2020_Data_Training"
output_trainImage = "your-Path_to/trainImage"
output_trainMask = "your-Path_to/trainMask"
And runsrc/train.py
,change data_path.Began to run
data_path = 'your-Path_to'
Runsrc/inference.py
,to restore the picture.
Runsrc/test.py
.Test it.
训练集评价指标
|
ET |
WT |
TC |
Mean |
Dice |
0.79655 |
0.93 |
0.90825 |
0.878267 |
Sensitivity |
0.78583 |
0.91073 |
0.91593 |
0.87083 |
Specificity |
0.99978 |
0.99959 |
0.9996 |
0.999657 |
Hausdorff95 |
22.91558 |
3.84997 |
3.74955 |
10.1717 |
验证集评价指标
|
ET |
WT |
TC |
Mean |
Dice |
0.71534 |
0.89413 |
0.80496 |
0.80481 |
Sensitivity |
0.70984 |
0.88827 |
0.81775 |
0.805287 |
Specificity |
0.99971 |
0.99917 |
0.99938 |
0.99942 |
Hausdorff95 |
36.16794 |
4.63229 |
9.53405 |
16.77809 |