Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

hc-leipzig-7t-mp2rage graphs #76

Draft
wants to merge 10 commits into
base: main
Choose a base branch
from
Draft

hc-leipzig-7t-mp2rage graphs #76

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
10 commits
Select commit Hold shift + click to select a range
c8fc1c5
New script for nnUNet training-logs visualization
KaterinaKrejci231054 Aug 30, 2024
0625376
Update training/hc-leipzig-7t-mp2rage/plot_nnunet_different_training_…
KaterinaKrejci231054 Aug 30, 2024
0b9c6e1
Update training/hc-leipzig-7t-mp2rage/plot_nnunet_different_training_…
KaterinaKrejci231054 Aug 30, 2024
352831d
Chaged description and help
KaterinaKrejci231054 Aug 30, 2024
1ffd52a
New script for train-val split for nnUNet splits_final.json file
KaterinaKrejci231054 Jan 15, 2025
5345ad2
New script for train-val-test split - saved as .csv file
KaterinaKrejci231054 Jan 15, 2025
239bb4d
New file for train-val split for mp2rage models
KaterinaKrejci231054 Jan 15, 2025
662fddc
Final train-val-test splits for mp2rage models (5 fold cross-val)
KaterinaKrejci231054 Jan 15, 2025
b7f5e65
Merge branch 'main' into kk/hc-leipzig-7t-mp2rage_graphs
valosekj Jan 15, 2025
53b3da3
Changed settings of plots
KaterinaKrejci231054 Jan 26, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
257 changes: 257 additions & 0 deletions training/hc-leipzig-7t-mp2rage/hc-leipzig-7t-mp2rage_fold_splits.json
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,257 @@
[
{
"train": [
"SCDATA_18_inv-1_part-mag_MP2RAGE",
"SCDATA_18_inv-2_part-mag_MP2RAGE",
"SCDATA_18_UNIT1",
"SCDATA_19_inv-1_part-mag_MP2RAGE",
"SCDATA_19_inv-2_part-mag_MP2RAGE",
"SCDATA_19_UNIT1",
"SCDATA_20_inv-1_part-mag_MP2RAGE",
"SCDATA_20_inv-2_part-mag_MP2RAGE",
"SCDATA_20_UNIT1",
"SCDATA_22_inv-1_part-mag_MP2RAGE",
"SCDATA_22_inv-2_part-mag_MP2RAGE",
"SCDATA_22_UNIT1",
"SCDATA_23_inv-1_part-mag_MP2RAGE",
"SCDATA_23_inv-2_part-mag_MP2RAGE",
"SCDATA_23_UNIT1",
"SCDATA_27_inv-1_part-mag_MP2RAGE",
"SCDATA_27_inv-2_part-mag_MP2RAGE",
"SCDATA_27_UNIT1",
"SCDATA_28_inv-1_part-mag_MP2RAGE",
"SCDATA_28_inv-2_part-mag_MP2RAGE",
"SCDATA_28_UNIT1",
"SCDATA_30_inv-1_part-mag_MP2RAGE",
"SCDATA_30_inv-2_part-mag_MP2RAGE",
"SCDATA_30_UNIT1",
"SCDATA_38_inv-1_part-mag_MP2RAGE",
"SCDATA_38_inv-2_part-mag_MP2RAGE",
"SCDATA_38_UNIT1",
"SCDATA_39_inv-1_part-mag_MP2RAGE",
"SCDATA_39_inv-2_part-mag_MP2RAGE",
"SCDATA_39_UNIT1",
"SCDATA_40_inv-1_part-mag_MP2RAGE",
"SCDATA_40_inv-2_part-mag_MP2RAGE",
"SCDATA_40_UNIT1",
"SCDATA_41_inv-1_part-mag_MP2RAGE",
"SCDATA_41_inv-2_part-mag_MP2RAGE",
"SCDATA_41_UNIT1"
],
"val": [
"SCDATA_25_inv-1_part-mag_MP2RAGE",
"SCDATA_25_inv-2_part-mag_MP2RAGE",
"SCDATA_25_UNIT1",
"SCDATA_29_inv-1_part-mag_MP2RAGE",
"SCDATA_29_inv-2_part-mag_MP2RAGE",
"SCDATA_29_UNIT1",
"SCDATA_36_inv-1_part-mag_MP2RAGE",
"SCDATA_36_inv-2_part-mag_MP2RAGE",
"SCDATA_36_UNIT1"
]
},
{
"train": [
"SCDATA_19_inv-1_part-mag_MP2RAGE",
"SCDATA_19_inv-2_part-mag_MP2RAGE",
"SCDATA_19_UNIT1",
"SCDATA_22_inv-1_part-mag_MP2RAGE",
"SCDATA_22_inv-2_part-mag_MP2RAGE",
"SCDATA_22_UNIT1",
"SCDATA_23_inv-1_part-mag_MP2RAGE",
"SCDATA_23_inv-2_part-mag_MP2RAGE",
"SCDATA_23_UNIT1",
"SCDATA_25_inv-1_part-mag_MP2RAGE",
"SCDATA_25_inv-2_part-mag_MP2RAGE",
"SCDATA_25_UNIT1",
"SCDATA_27_inv-1_part-mag_MP2RAGE",
"SCDATA_27_inv-2_part-mag_MP2RAGE",
"SCDATA_27_UNIT1",
"SCDATA_28_inv-1_part-mag_MP2RAGE",
"SCDATA_28_inv-2_part-mag_MP2RAGE",
"SCDATA_28_UNIT1",
"SCDATA_29_inv-1_part-mag_MP2RAGE",
"SCDATA_29_inv-2_part-mag_MP2RAGE",
"SCDATA_29_UNIT1",
"SCDATA_30_inv-1_part-mag_MP2RAGE",
"SCDATA_30_inv-2_part-mag_MP2RAGE",
"SCDATA_30_UNIT1",
"SCDATA_36_inv-1_part-mag_MP2RAGE",
"SCDATA_36_inv-2_part-mag_MP2RAGE",
"SCDATA_36_UNIT1",
"SCDATA_38_inv-1_part-mag_MP2RAGE",
"SCDATA_38_inv-2_part-mag_MP2RAGE",
"SCDATA_38_UNIT1",
"SCDATA_40_inv-1_part-mag_MP2RAGE",
"SCDATA_40_inv-2_part-mag_MP2RAGE",
"SCDATA_40_UNIT1",
"SCDATA_41_inv-1_part-mag_MP2RAGE",
"SCDATA_41_inv-2_part-mag_MP2RAGE",
"SCDATA_41_UNIT1"
],
"val": [
"SCDATA_18_inv-1_part-mag_MP2RAGE",
"SCDATA_18_inv-2_part-mag_MP2RAGE",
"SCDATA_18_UNIT1",
"SCDATA_20_inv-1_part-mag_MP2RAGE",
"SCDATA_20_inv-2_part-mag_MP2RAGE",
"SCDATA_20_UNIT1",
"SCDATA_39_inv-1_part-mag_MP2RAGE",
"SCDATA_39_inv-2_part-mag_MP2RAGE",
"SCDATA_39_UNIT1"
]
},
{
"train": [
"SCDATA_18_inv-1_part-mag_MP2RAGE",
"SCDATA_18_inv-2_part-mag_MP2RAGE",
"SCDATA_18_UNIT1",
"SCDATA_20_inv-1_part-mag_MP2RAGE",
"SCDATA_20_inv-2_part-mag_MP2RAGE",
"SCDATA_20_UNIT1",
"SCDATA_22_inv-1_part-mag_MP2RAGE",
"SCDATA_22_inv-2_part-mag_MP2RAGE",
"SCDATA_22_UNIT1",
"SCDATA_23_inv-1_part-mag_MP2RAGE",
"SCDATA_23_inv-2_part-mag_MP2RAGE",
"SCDATA_23_UNIT1",
"SCDATA_25_inv-1_part-mag_MP2RAGE",
"SCDATA_25_inv-2_part-mag_MP2RAGE",
"SCDATA_25_UNIT1",
"SCDATA_27_inv-1_part-mag_MP2RAGE",
"SCDATA_27_inv-2_part-mag_MP2RAGE",
"SCDATA_27_UNIT1",
"SCDATA_28_inv-1_part-mag_MP2RAGE",
"SCDATA_28_inv-2_part-mag_MP2RAGE",
"SCDATA_28_UNIT1",
"SCDATA_29_inv-1_part-mag_MP2RAGE",
"SCDATA_29_inv-2_part-mag_MP2RAGE",
"SCDATA_29_UNIT1",
"SCDATA_30_inv-1_part-mag_MP2RAGE",
"SCDATA_30_inv-2_part-mag_MP2RAGE",
"SCDATA_30_UNIT1",
"SCDATA_36_inv-1_part-mag_MP2RAGE",
"SCDATA_36_inv-2_part-mag_MP2RAGE",
"SCDATA_36_UNIT1",
"SCDATA_38_inv-1_part-mag_MP2RAGE",
"SCDATA_38_inv-2_part-mag_MP2RAGE",
"SCDATA_38_UNIT1",
"SCDATA_39_inv-1_part-mag_MP2RAGE",
"SCDATA_39_inv-2_part-mag_MP2RAGE",
"SCDATA_39_UNIT1"
],
"val": [
"SCDATA_19_inv-1_part-mag_MP2RAGE",
"SCDATA_19_inv-2_part-mag_MP2RAGE",
"SCDATA_19_UNIT1",
"SCDATA_40_inv-1_part-mag_MP2RAGE",
"SCDATA_40_inv-2_part-mag_MP2RAGE",
"SCDATA_40_UNIT1",
"SCDATA_41_inv-1_part-mag_MP2RAGE",
"SCDATA_41_inv-2_part-mag_MP2RAGE",
"SCDATA_41_UNIT1"
]
},
{
"train": [
"SCDATA_18_inv-1_part-mag_MP2RAGE",
"SCDATA_18_inv-2_part-mag_MP2RAGE",
"SCDATA_18_UNIT1",
"SCDATA_19_inv-1_part-mag_MP2RAGE",
"SCDATA_19_inv-2_part-mag_MP2RAGE",
"SCDATA_19_UNIT1",
"SCDATA_20_inv-1_part-mag_MP2RAGE",
"SCDATA_20_inv-2_part-mag_MP2RAGE",
"SCDATA_20_UNIT1",
"SCDATA_23_inv-1_part-mag_MP2RAGE",
"SCDATA_23_inv-2_part-mag_MP2RAGE",
"SCDATA_23_UNIT1",
"SCDATA_25_inv-1_part-mag_MP2RAGE",
"SCDATA_25_inv-2_part-mag_MP2RAGE",
"SCDATA_25_UNIT1",
"SCDATA_27_inv-1_part-mag_MP2RAGE",
"SCDATA_27_inv-2_part-mag_MP2RAGE",
"SCDATA_27_UNIT1",
"SCDATA_29_inv-1_part-mag_MP2RAGE",
"SCDATA_29_inv-2_part-mag_MP2RAGE",
"SCDATA_29_UNIT1",
"SCDATA_30_inv-1_part-mag_MP2RAGE",
"SCDATA_30_inv-2_part-mag_MP2RAGE",
"SCDATA_30_UNIT1",
"SCDATA_36_inv-1_part-mag_MP2RAGE",
"SCDATA_36_inv-2_part-mag_MP2RAGE",
"SCDATA_36_UNIT1",
"SCDATA_39_inv-1_part-mag_MP2RAGE",
"SCDATA_39_inv-2_part-mag_MP2RAGE",
"SCDATA_39_UNIT1",
"SCDATA_40_inv-1_part-mag_MP2RAGE",
"SCDATA_40_inv-2_part-mag_MP2RAGE",
"SCDATA_40_UNIT1",
"SCDATA_41_inv-1_part-mag_MP2RAGE",
"SCDATA_41_inv-2_part-mag_MP2RAGE",
"SCDATA_41_UNIT1"
],
"val": [
"SCDATA_22_inv-1_part-mag_MP2RAGE",
"SCDATA_22_inv-2_part-mag_MP2RAGE",
"SCDATA_22_UNIT1",
"SCDATA_28_inv-1_part-mag_MP2RAGE",
"SCDATA_28_inv-2_part-mag_MP2RAGE",
"SCDATA_28_UNIT1",
"SCDATA_38_inv-1_part-mag_MP2RAGE",
"SCDATA_38_inv-2_part-mag_MP2RAGE",
"SCDATA_38_UNIT1"
]
},
{
"train": [
"SCDATA_18_inv-1_part-mag_MP2RAGE",
"SCDATA_18_inv-2_part-mag_MP2RAGE",
"SCDATA_18_UNIT1",
"SCDATA_19_inv-1_part-mag_MP2RAGE",
"SCDATA_19_inv-2_part-mag_MP2RAGE",
"SCDATA_19_UNIT1",
"SCDATA_20_inv-1_part-mag_MP2RAGE",
"SCDATA_20_inv-2_part-mag_MP2RAGE",
"SCDATA_20_UNIT1",
"SCDATA_22_inv-1_part-mag_MP2RAGE",
"SCDATA_22_inv-2_part-mag_MP2RAGE",
"SCDATA_22_UNIT1",
"SCDATA_25_inv-1_part-mag_MP2RAGE",
"SCDATA_25_inv-2_part-mag_MP2RAGE",
"SCDATA_25_UNIT1",
"SCDATA_28_inv-1_part-mag_MP2RAGE",
"SCDATA_28_inv-2_part-mag_MP2RAGE",
"SCDATA_28_UNIT1",
"SCDATA_29_inv-1_part-mag_MP2RAGE",
"SCDATA_29_inv-2_part-mag_MP2RAGE",
"SCDATA_29_UNIT1",
"SCDATA_36_inv-1_part-mag_MP2RAGE",
"SCDATA_36_inv-2_part-mag_MP2RAGE",
"SCDATA_36_UNIT1",
"SCDATA_38_inv-1_part-mag_MP2RAGE",
"SCDATA_38_inv-2_part-mag_MP2RAGE",
"SCDATA_38_UNIT1",
"SCDATA_39_inv-1_part-mag_MP2RAGE",
"SCDATA_39_inv-2_part-mag_MP2RAGE",
"SCDATA_39_UNIT1",
"SCDATA_40_inv-1_part-mag_MP2RAGE",
"SCDATA_40_inv-2_part-mag_MP2RAGE",
"SCDATA_40_UNIT1",
"SCDATA_41_inv-1_part-mag_MP2RAGE",
"SCDATA_41_inv-2_part-mag_MP2RAGE",
"SCDATA_41_UNIT1"
],
"val": [
"SCDATA_23_inv-1_part-mag_MP2RAGE",
"SCDATA_23_inv-2_part-mag_MP2RAGE",
"SCDATA_23_UNIT1",
"SCDATA_27_inv-1_part-mag_MP2RAGE",
"SCDATA_27_inv-2_part-mag_MP2RAGE",
"SCDATA_27_UNIT1",
"SCDATA_30_inv-1_part-mag_MP2RAGE",
"SCDATA_30_inv-2_part-mag_MP2RAGE",
"SCDATA_30_UNIT1"
]
}
]
26 changes: 26 additions & 0 deletions training/hc-leipzig-7t-mp2rage/hc-leipzig-7t-mp2rage_with_folds.csv
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,26 @@
Subject,Train/Test,Fold_1,Fold_2,Fold_3,Fold_4,Fold_5
sub-17,Test,Test,Test,Test,Test,Test
sub-18,Train,Train,Validation,Train,Train,Train
sub-19,Train,Train,Train,Validation,Train,Train
sub-20,Train,Train,Validation,Train,Train,Train
sub-21,Excluded,Excluded,Excluded,Excluded,Excluded,Excluded
sub-22,Train,Train,Train,Train,Validation,Train
sub-23,Train,Train,Train,Train,Train,Validation
sub-24,Test,Test,Test,Test,Test,Test
sub-25,Train,Validation,Train,Train,Train,Train
sub-26,Excluded,Excluded,Excluded,Excluded,Excluded,Excluded
sub-27,Train,Train,Train,Train,Train,Validation
sub-28,Train,Train,Train,Train,Validation,Train
sub-29,Train,Validation,Train,Train,Train,Train
sub-30,Train,Train,Train,Train,Train,Validation
sub-31,Test,Test,Test,Test,Test,Test
sub-32,Excluded,Excluded,Excluded,Excluded,Excluded,Excluded
sub-33,Excluded,Excluded,Excluded,Excluded,Excluded,Excluded
sub-34,Excluded,Excluded,Excluded,Excluded,Excluded,Excluded
sub-35,Excluded,Excluded,Excluded,Excluded,Excluded,Excluded
sub-36,Train,Validation,Train,Train,Train,Train
sub-37,Test,Test,Test,Test,Test,Test
sub-38,Train,Train,Train,Train,Validation,Train
sub-39,Train,Train,Validation,Train,Train,Train
sub-40,Train,Train,Train,Validation,Train,Train
sub-41,Train,Train,Train,Validation,Train,Train
70 changes: 70 additions & 0 deletions training/hc-leipzig-7t-mp2rage/nnUNetv2_mp2rage_random_train_val_split_to_json.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,70 @@
import pandas as pd
import numpy as np
from sklearn.model_selection import KFold
import json

# Load the data from the CSV file
train_test_dataframe = pd.read_csv('hc-leipzig-7t-mp2rage_train-test_split.csv')

# Get the training data only
train_dataframe = train_test_dataframe[train_test_dataframe['Train/Test'] == 'Train']

# Extract unique subjects and rename them to SCDATA_<number>
subjects = train_dataframe['Subject'].unique()[:]

# Get only number from the subject name
subjects = [int(subj.split('-')[1]) for subj in subjects]

# Rename the subjects
renamed_subjects = [f"SCDATA_{subj}" for subj in subjects]
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

do we need to do this renaming? by doing it, the output csv file contains sub- but the output json file contains SCDATA. this is confusing. I would stick with the original filenames: sub-


# Define the possible contrasts for each subject
contrasts = ["inv-1_part-mag_MP2RAGE", "inv-2_part-mag_MP2RAGE", "UNIT1"]

# Expand subjects to include all contrasts
expanded_subjects = []
for subject in renamed_subjects:
for contrast in contrasts:
expanded_subjects.append(f"{subject}_{contrast}")

# Convert expanded_subjects into a numpy array for indexing
expanded_subjects = np.array(expanded_subjects)

# Initialize 5-fold cross-validation
kf = KFold(n_splits=5, shuffle=True, random_state=7)

# Prepare the dataframe for CSV and a list for JSON
folded_dataframe = pd.DataFrame({"Subject": expanded_subjects})
fold_splits = []

# Add columns for each fold
for fold, (train_index, val_index) in enumerate(kf.split(renamed_subjects), start=1):
# Get the train and validation subjects
train_subjects = [renamed_subjects[idx] for idx in train_index]
val_subjects = [renamed_subjects[idx] for idx in val_index]

# Expand train and validation subjects with all contrasts
train_expanded = [f"{subj}_{contrast}" for subj in train_subjects for contrast in contrasts]
val_expanded = [f"{subj}_{contrast}" for subj in val_subjects for contrast in contrasts]

# Save the split for JSON
fold_splits.append({
"train": train_expanded,
"val": val_expanded
})

# Add a new column to the dataframe indicating fold membership
fold_column = f'Fold_{fold}'
folded_dataframe[fold_column] = 'Excluded' # Initialize with 'Excluded'
folded_dataframe.loc[folded_dataframe['Subject'].isin(train_expanded), fold_column] = 'Train'
folded_dataframe.loc[folded_dataframe['Subject'].isin(val_expanded), fold_column] = 'Validation'

# Save the splits to a JSON file
with open('hc-leipzig-7t-mp2rage_fold_splits.json', 'w') as json_file:
json.dump(fold_splits, json_file, indent=4)

# Print confirmation message
print("Renamed and expanded fold splits saved to 'hc-leipzig-7t-mp2rage_fold_splits_expanded_renamed.json'")

# Display the first few rows of the updated dataframe
print(folded_dataframe.head())
Loading