DataSET_module

Module containing dataset functionalities.

1. SPlit datasets into folds
2. Generate dataset characteristics and meta properties 3.Generating distance maps, computing border irregularity index
3. Dataset Visualizations

Note: Right now the only public scripts are the ones used to split the dataset into folds.

Requirements:

1. cv2
2. torch,
3. numpy,
4. scipy,
5. random

KFOLD-Split_Dataset: Script to divide the data into folds,

• Import the required dataset class from DataSEt_Classes and initialize an instance of the class ds.
• place the data ensembles (imagesTr, labelsTr) from decathlon in nifty/root.

variables to initialize

• typ = 'ROOT': the root folder you want your downloaded dataset to be in. preferably place it in ROOT.
• root_path: the root directory leading to your data.
• fold: the name of the target fold
• nb_val: the number of validation samples (recommended to be 20% of the total training set)