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AbdelrahmanShakerYousefAbdelrahmanShakerYousef
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Add Lung & Tumor datasets
1 parent 0e30f5a commit d896dd5

32 files changed

+5193
-66
lines changed

‎eval_synapse.sh

-15
This file was deleted.

‎run_evaluation_acdc.sh ‎evaluation_scripts/run_evaluation_acdc.sh

+4-4
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@@ -1,11 +1,11 @@
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#!/bin/sh
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DATASET_PATH=DATASET
4-
CHECKPOINT_PATH=unetr_pp/evaluation/unetr_pp_acdc_checkpoint
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DATASET_PATH=../DATASET_Acdc
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CHECKPOINT_PATH=../unetr_pp/evaluation/unetr_pp_acdc_checkpoint
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6-
export PYTHONPATH=./
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export PYTHONPATH=.././
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export RESULTS_FOLDER="$CHECKPOINT_PATH"
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export unetr_pp_preprocessed="$DATASET_PATH"/unetr_pp_raw/unetr_pp_raw_data/Task01_ACDC
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export unetr_pp_raw_data_base="$DATASET_PATH"/unetr_pp_raw
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11-
python unetr_pp/run/run_training.py 3d_fullres unetr_pp_trainer_acdc 1 0 -val
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python ../unetr_pp/run/run_training.py 3d_fullres unetr_pp_trainer_acdc 1 0 -val

‎evaluation_scripts/run_evaluation_lung.sh

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#!/bin/sh
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DATASET_PATH=../DATASET_Lungs
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CHECKPOINT_PATH=../unetr_pp/evaluation/unetr_pp_lung_checkpoint
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export PYTHONPATH=.././
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export RESULTS_FOLDER="$CHECKPOINT_PATH"
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export unetr_pp_preprocessed="$DATASET_PATH"/unetr_pp_raw/unetr_pp_raw_data/Task06_Lung
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export unetr_pp_raw_data_base="$DATASET_PATH"/unetr_pp_raw
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python ../unetr_pp/run/run_training.py 3d_fullres unetr_pp_trainer_lung 6 0 -val

‎evaluation_scripts/run_evaluation_synapse.sh

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#!/bin/sh
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DATASET_PATH=../DATASET_Synapse
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CHECKPOINT_PATH=../unetr_pp/evaluation/unetr_pp_synapse_checkpoint
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export PYTHONPATH=.././
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export RESULTS_FOLDER="$CHECKPOINT_PATH"
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export unetr_pp_preprocessed="$DATASET_PATH"/unetr_pp_raw/unetr_pp_raw_data/Task02_Synapse
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export unetr_pp_raw_data_base="$DATASET_PATH"/unetr_pp_raw
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python ../unetr_pp/run/run_training.py 3d_fullres unetr_pp_trainer_synapse 2 0 -val

‎evaluation_scripts/run_evaluation_tumor.sh

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#!/bin/sh
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DATASET_PATH=../DATASET_Tumor
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export PYTHONPATH=.././
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export RESULTS_FOLDER=../unetr_pp/evaluation/unetr_pp_tumor_checkpoint
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export unetr_pp_preprocessed="$DATASET_PATH"/unetr_pp_raw/unetr_pp_raw_data/Task03_tumor
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export unetr_pp_raw_data_base="$DATASET_PATH"/unetr_pp_raw
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# Only for Tumor, it is recommended to train unetr_plus_plus first, and then use the provided checkpoint to evaluate. It might raise issues regarding the pickle files if you evaluated without training
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python ../unetr_pp/inference/predict_simple.py -i ../unetr_plus_plus/DATASET_Tumor/unetr_pp_raw/unetr_pp_raw_data/Task003_tumor/imagesTs -o ../unetr_plus_plus/unetr_pp/evaluation/unetr_pp_tumor_checkpoint/inferTs -m 3d_fullres -t 3 -f 0 -chk model_final_checkpoint -tr unetr_pp_trainer_tumor
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python ../unetr_pp/inference_tumor.py 0
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‎run_evaluation_synapse.sh

-11
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‎run_training_acdc.sh

-10
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‎run_training_synapse.sh

-10
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‎training_scripts/run_training_acdc.sh

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#!/bin/sh
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DATASET_PATH=../DATASET_Acdc
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export PYTHONPATH=.././
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export RESULTS_FOLDER=../output_acdc
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export unetr_pp_preprocessed="$DATASET_PATH"/unetr_pp_raw/unetr_pp_raw_data/Task01_ACDC
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export unetr_pp_raw_data_base="$DATASET_PATH"/unetr_pp_raw
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python ../unetr_pp/run/run_training.py 3d_fullres unetr_pp_trainer_acdc 1 0

‎training_scripts/run_training_lung.sh

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#!/bin/sh
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DATASET_PATH=../DATASET_Lungs
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export PYTHONPATH=.././
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export RESULTS_FOLDER=../output_lung
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export unetr_pp_preprocessed="$DATASET_PATH"/unetr_pp_raw/unetr_pp_raw_data/Task06_Lung
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export unetr_pp_raw_data_base="$DATASET_PATH"/unetr_pp_raw
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python ../unetr_pp/run/run_training.py 3d_fullres unetr_pp_trainer_lung 6 0

‎training_scripts/run_training_synapse.sh

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#!/bin/sh
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DATASET_PATH=../DATASET_Synapse
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export PYTHONPATH=.././
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export RESULTS_FOLDER=../output_synapse
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export unetr_pp_preprocessed="$DATASET_PATH"/unetr_pp_raw/unetr_pp_raw_data/Task02_Synapse
8+
export unetr_pp_raw_data_base="$DATASET_PATH"/unetr_pp_raw
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python ../unetr_pp/run/run_training.py 3d_fullres unetr_pp_trainer_synapse 2 0

‎training_scripts/run_training_tumor.sh

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#!/bin/sh
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DATASET_PATH=../DATASET_Tumor
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export PYTHONPATH=.././
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export RESULTS_FOLDER=../output_tumor
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export unetr_pp_preprocessed="$DATASET_PATH"/unetr_pp_raw/unetr_pp_raw_data/Task03_tumor
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export unetr_pp_raw_data_base="$DATASET_PATH"/unetr_pp_raw
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python ../unetr_pp/run/run_training.py 3d_fullres unetr_pp_trainer_tumor 3 0

‎unetr_pp/evaluation/unetr_pp_lung_checkpoint/unetr_pp/3d_fullres/Task006_Lung/unetr_pp_trainer_lung__unetr_pp_Plansv2.1/fold_0/.gitignore

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# Ignore everything in this directory
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*
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# Except this file
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!.gitignore

‎unetr_pp/evaluation/unetr_pp_tumor_checkpoint/unetr_pp/3d_fullres/Task003_tumor/unetr_pp_trainer_tumor__unetr_pp_Plansv2.1/fold_0/.gitignore

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# Ignore everything in this directory
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*
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# Except this file
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!.gitignore

‎unetr_pp/inference/predict_simple.py

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@@ -17,7 +17,7 @@
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import torch
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from unetr_pp.inference.predict import predict_from_folder
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from unetr_pp.paths import default_plans_identifier, network_training_output_dir, default_cascade_trainer, default_trainer
20+
from unetr_pp.paths import default_plans_identifier, network_training_output_dir, default_trainer
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from batchgenerators.utilities.file_and_folder_operations import join, isdir
2222
from unetr_pp.utilities.task_name_id_conversion import convert_id_to_task_name
2323
from unetr_pp.paths import network_training_output_dir, preprocessing_output_dir, default_plans_identifier
@@ -46,8 +46,8 @@ def main():
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default=default_trainer)
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parser.add_argument('-ctr', '--cascade_trainer_class_name',
4848
help="Trainer class name used for predicting the 3D full resolution U-Net part of the cascade."
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"Default is %s" % default_cascade_trainer, required=False,
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default=default_cascade_trainer)
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"Default is %s" % default_trainer, required=False,
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default=default_trainer)
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parser.add_argument('-m', '--model', help="2d, 3d_lowres, 3d_fullres or 3d_cascade_fullres. Default: 3d_fullres",
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default="3d_fullres", required=False)

‎unetr_pp/inference_synapse.py

+7-5
Original file line numberDiff line numberDiff line change
@@ -32,10 +32,12 @@ def process_label(label):
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return spleen,right_kidney,left_kidney,gallbladder,liver,stomach,aorta,pancreas
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35-
def test(fold):
36-
path=None #Task002_Synapse path
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label_list=sorted(glob.glob(os.path.join(path,'labelsTs','*nii.gz')))
38-
infer_list=sorted(glob.glob(os.path.join(path,'inferTs','nnformer_synapse','*nii.gz')))
35+
def test(fold):
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label_path= None # Replace None by full path of "DATASET/unetr_pp_raw/unetr_pp_raw_data/Task002_Synapse/"
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infer_path = None # Replace None by full path of "output_synapse"
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label_list=sorted(glob.glob(os.path.join(label_path,'labelsTs','*nii.gz')))
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infer_list=sorted(glob.glob(os.path.join(infer_path,'inferTs','*nii.gz')))
3941
print("loading success...")
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print(label_list)
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print(infer_list)
@@ -57,7 +59,7 @@ def test(fold):
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hd_aorta=[]
5860
hd_pancreas=[]
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60-
file=path + 'inferTs/'+fold
62+
file=infer_path + 'inferTs/'+fold
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if not os.path.exists(file):
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os.makedirs(file)
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fw = open(file+'/dice_pre.txt', 'a')

‎unetr_pp/inference_tumor.py

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@@ -0,0 +1,143 @@
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import glob
2+
import os
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import SimpleITK as sitk
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import numpy as np
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import argparse
6+
from medpy.metric import binary
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8+
def read_nii(path):
9+
return sitk.GetArrayFromImage(sitk.ReadImage(path))
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11+
def new_dice(pred,label):
12+
tp_hard = np.sum((pred == 1).astype(np.float) * (label == 1).astype(np.float))
13+
fp_hard = np.sum((pred == 1).astype(np.float) * (label != 1).astype(np.float))
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fn_hard = np.sum((pred != 1).astype(np.float) * (label == 1).astype(np.float))
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return 2*tp_hard/(2*tp_hard+fp_hard+fn_hard)
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17+
def dice(pred, label):
18+
if (pred.sum() + label.sum()) == 0:
19+
return 1
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else:
21+
return 2. * np.logical_and(pred, label).sum() / (pred.sum() + label.sum())
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23+
def hd(pred,gt):
24+
if pred.sum() > 0 and gt.sum()>0:
25+
hd95 = binary.hd95(pred, gt)
26+
return hd95
27+
else:
28+
return 0
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30+
def process_label(label):
31+
net = label == 2
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ed = label == 1
33+
et = label == 3
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ET=et
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TC=net+et
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WT=net+et+ed
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ED= ed
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NET=net
39+
return ET,TC,WT,ED,NET
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41+
def test(fold):
42+
#path='./'
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44+
path = None # Replace None by the full path of : unetr_plus_plus/DATASET_Tumor/unetr_pp_raw/unetr_pp_raw_data/Task03_tumor/"
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label_list=sorted(glob.glob(os.path.join(path,'labelsTs','*nii.gz')))
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infer_path = None # Replace None by the full path of : unetr_plus_plus/unetr_pp/evaluation/unetr_pp_tumor_checkpoint/"
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50+
infer_list=sorted(glob.glob(os.path.join(infer_path,'inferTs','*nii.gz')))
51+
print("loading success...")
52+
Dice_et=[]
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Dice_tc=[]
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Dice_wt=[]
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Dice_ed=[]
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Dice_net=[]
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HD_et=[]
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HD_tc=[]
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HD_wt=[]
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HD_ed=[]
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HD_net=[]
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file=infer_path + 'inferTs/'+fold
64+
if not os.path.exists(file):
65+
os.makedirs(file)
66+
fw = open(file+'/dice_five.txt', 'w')
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68+
for label_path,infer_path in zip(label_list,infer_list):
69+
print(label_path.split('/')[-1])
70+
print(infer_path.split('/')[-1])
71+
label,infer = read_nii(label_path),read_nii(infer_path)
72+
label_et,label_tc,label_wt,label_ed,label_net=process_label(label)
73+
infer_et,infer_tc,infer_wt,infer_ed,infer_net=process_label(infer)
74+
Dice_et.append(dice(infer_et,label_et))
75+
Dice_tc.append(dice(infer_tc,label_tc))
76+
Dice_wt.append(dice(infer_wt,label_wt))
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Dice_ed.append(dice(infer_ed,label_ed))
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Dice_net.append(dice(infer_net,label_net))
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80+
HD_et.append(hd(infer_et,label_et))
81+
HD_tc.append(hd(infer_tc,label_tc))
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HD_wt.append(hd(infer_wt,label_wt))
83+
HD_ed.append(hd(infer_ed,label_ed))
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HD_net.append(hd(infer_net,label_net))
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87+
fw.write('*'*20+'\n',)
88+
fw.write(infer_path.split('/')[-1]+'\n')
89+
fw.write('hd_et: {:.4f}\n'.format(HD_et[-1]))
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fw.write('hd_tc: {:.4f}\n'.format(HD_tc[-1]))
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fw.write('hd_wt: {:.4f}\n'.format(HD_wt[-1]))
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fw.write('hd_ed: {:.4f}\n'.format(HD_ed[-1]))
93+
fw.write('hd_net: {:.4f}\n'.format(HD_net[-1]))
94+
fw.write('*'*20+'\n',)
95+
fw.write('Dice_et: {:.4f}\n'.format(Dice_et[-1]))
96+
fw.write('Dice_tc: {:.4f}\n'.format(Dice_tc[-1]))
97+
fw.write('Dice_wt: {:.4f}\n'.format(Dice_wt[-1]))
98+
fw.write('Dice_ed: {:.4f}\n'.format(Dice_ed[-1]))
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fw.write('Dice_net: {:.4f}\n'.format(Dice_net[-1]))
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101+
#print('dice_et: {:.4f}'.format(np.mean(Dice_et)))
102+
#print('dice_tc: {:.4f}'.format(np.mean(Dice_tc)))
103+
#print('dice_wt: {:.4f}'.format(np.mean(Dice_wt)))
104+
dsc=[]
105+
avg_hd=[]
106+
dsc.append(np.mean(Dice_et))
107+
dsc.append(np.mean(Dice_tc))
108+
dsc.append(np.mean(Dice_wt))
109+
dsc.append(np.mean(Dice_ed))
110+
dsc.append(np.mean(Dice_net))
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avg_hd.append(np.mean(HD_et))
114+
avg_hd.append(np.mean(HD_tc))
115+
avg_hd.append(np.mean(HD_wt))
116+
avg_hd.append(np.mean(HD_ed))
117+
avg_hd.append(np.mean(HD_net))
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119+
fw.write('Dice_et'+str(np.mean(Dice_et))+' '+'\n')
120+
fw.write('Dice_tc'+str(np.mean(Dice_tc))+' '+'\n')
121+
fw.write('Dice_wt'+str(np.mean(Dice_wt))+' '+'\n')
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fw.write('Dice_ed'+str(np.mean(Dice_ed))+' '+'\n')
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fw.write('Dice_net'+str(np.mean(Dice_net))+' '+'\n')
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125+
fw.write('HD_et'+str(np.mean(HD_et))+' '+'\n')
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fw.write('HD_tc'+str(np.mean(HD_tc))+' '+'\n')
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fw.write('HD_wt'+str(np.mean(HD_wt))+' '+'\n')
128+
fw.write('HD_ed'+str(np.mean(HD_ed))+' '+'\n')
129+
fw.write('HD_net'+str(np.mean(HD_net))+' '+'\n')
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131+
fw.write('Dice'+str(np.mean(dsc))+' '+'\n')
132+
fw.write('HD'+str(np.mean(avg_hd))+' '+'\n')
133+
#print('Dice'+str(np.mean(dsc))+' '+'\n')
134+
#print('HD'+str(np.mean(avg_hd))+' '+'\n')
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138+
if __name__ == '__main__':
139+
parser = argparse.ArgumentParser()
140+
parser.add_argument("fold", help="fold name")
141+
args = parser.parse_args()
142+
fold=args.fold
143+
test(fold)

‎unetr_pp/network_architecture/lung/__init__.py

Whitespace-only changes.

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