abdomenatlas

Author: FabianIsensee

nnunetv2/dataset_conversion/Dataset023_AbdomenAtlas1_1Mini.py

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+from batchgenerators.utilities.file_and_folder_operations import *
+import shutil
+from nnunetv2.dataset_conversion.generate_dataset_json import generate_dataset_json
+from nnunetv2.paths import nnUNet_raw
+
+if __name__ == '__main__':
+    """
+    Download the dataset from huggingface:
+    https://huggingface.co/datasets/AbdomenAtlas/_AbdomenAtlas1.1Mini#3--download-the-dataset
+    
+    IMPORTANT
+    cases 5196-9262 currently do not have images, just the segmentation. This seems to be a mistake 
+    """
+    base = '/home/isensee/Downloads/AbdomenAtlas/uncompressed'
+    target_dataset_id = 23
+    target_dataset_name = f'Dataset{target_dataset_id:03.0f}_AbdomenAtlas1.1Mini'
+
+    cases = subdirs(base, join=False, prefix='BDMAP')
+
+    maybe_mkdir_p(join(nnUNet_raw, target_dataset_name))
+    imagesTr = join(nnUNet_raw, target_dataset_name, 'imagesTr')
+    labelsTr = join(nnUNet_raw, target_dataset_name, 'labelsTr')
+    maybe_mkdir_p(imagesTr)
+    maybe_mkdir_p(labelsTr)
+
+    for case in cases:
+        if not isfile(join(base, case, 'ct.nii.gz')):
+            print(f'Skipping case {case} due to missing image')
+            continue
+        shutil.copy(join(base, case, 'ct.nii.gz'), join(imagesTr, case + '_0000.nii.gz'))
+        shutil.copy(join(base, case, 'combined_labels.nii.gz'), join(labelsTr, case + '.nii.gz'))
+
+    class_map = {1: 'aorta', 2: 'gall_bladder', 3: 'kidney_left', 4: 'kidney_right', 5: 'liver',
+                 6: 'pancreas', 7: 'postcava', 8: 'spleen', 9: 'stomach', 10: 'adrenal_gland_left',
+                 11: 'adrenal_gland_right', 12: 'bladder', 13: 'celiac_trunk', 14: 'colon', 15: 'duodenum',
+                 16: 'esophagus', 17: 'femur_left', 18: 'femur_right', 19: 'hepatic_vessel', 20: 'intestine',
+                 21: 'lung_left', 22: 'lung_right', 23: 'portal_vein_and_splenic_vein',
+                 24: 'prostate', 25: 'rectum'}
+    labels = {
+        j: i for i, j in class_map.items()
+    }
+    labels['background'] = 0
+
+    generate_dataset_json(
+        join(nnUNet_raw, target_dataset_name),
+        {0: 'CT'},
+        labels,
+        len(cases),
+        '.nii.gz',
+        None,
+        target_dataset_name,
+        overwrite_image_reader_writer='NibabelIOWithReorient',
+        reference='https://huggingface.co/datasets/AbdomenAtlas/_AbdomenAtlas1.1Mini',
+        license='Creative Commons Attribution Non Commercial Share Alike 4.0; see reference'
+    )