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Dataset009_LUNA25/examples/dataset.json

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+{
+    "channel_names": {
+        "0": "CT"
+    },
+    "labels": {
+        "background": 0,
+        "nodule": 1
+    },
+    "classification_labels": {
+        "malignancy": {
+            "0": "Benign",
+            "1": "Malignant"
+        }
+    },
+    "numTraining": 6141,
+    "file_ending": ".nii.gz",
+    "name": "Dataset009_LUNA25",
+    "description": "LUNA25 — cropped low-dose chest CT patches for lung nodule segmentation and malignancy risk estimation (6141 nodule crops from lung cancer screening CTs)",
+    "reference": "Peeters D, Obreja B, Antonissen N, Jacobs C. Benchmarking of Artificial Intelligence and Radiologists for Lung Cancer Screening in CT: The LUNA25 Challenge. Medical Image Computing and Computer Assisted Intervention 2025 (MICCAI). Zenodo. 2025. https://doi.org/10.5281/zenodo.15094631",
+    "licence": "CC BY 4.0",
+    "release": "1.0"
+}