| { | |
| "channel_names": { | |
| "0": "t1c", | |
| "1": "t1n", | |
| "2": "t2f", | |
| "3": "t2w" | |
| }, | |
| "labels": { | |
| "background": 0, | |
| "NCR": 1, | |
| "ED": 2, | |
| "ET": 3, | |
| "NET_RC": 4 | |
| }, | |
| "classification_labels": { | |
| "primary_diagnosis": { | |
| "0": "GBM", | |
| "1": "Astrocytoma", | |
| "2": "Others" | |
| } | |
| }, | |
| "numTraining": 591, | |
| "file_ending": ".nii.gz", | |
| "overwrite_image_reader_writer": "SimpleITKIO", | |
| "license": "CC-BY-NC 4.0", | |
| "description": "MU-Glioma-Post — post-treatment glioma multi-sequence MRI (t1c, t1n, t2f, t2w) with tumor segmentation and primary diagnosis classification (591 timepoints from 203 patients)", | |
| "reference": "Mahmoud E, Gass J, Dhemesh Y, Greaser J, Pogorzelski K, Isufi E, Garrett F, Thacker J, Tahon NH, Sinclair J, Layfield L. MU-Glioma Post: A comprehensive dataset of automated MR multi-sequence segmentation and clinical features. Scientific data. 2025 Nov 20;12(1):1847.", | |
| "name": "Dataset005_MU_Glioma_Post", | |
| "release": "1.0" | |
| } | |