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--- |
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license: mit |
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task_categories: |
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- image-classification |
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- feature-extraction |
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tags: |
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- biology |
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- medical |
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pretty_name: AAL Statistics Volumn |
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size_categories: |
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- n<1K |
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language: |
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- en |
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--- |
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# Dataset Card for "MuGemSt/AAL_statistics_volumn" |
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The AAL (Automated Anatomical Labeling) Statistical Volume Dataset provides a comprehensive collection of brain volume measurements based on AAL atlases. It covers statistical information on brain regions derived from structural magnetic resonance imaging (MRI) scans. Researchers commonly utilize this dataset for studies related to neuroimaging, neuroscience, and structural analysis of the brain.The AAL Statistical Volume Dataset plays a key role in advancing our understanding of brain anatomy by supporting the development and evaluation of automated brain region identification and volume analysis algorithms. With its wealth of volumetric data from diverse individuals, the dataset provides an invaluable resource for studies aimed at characterizing structural changes in the brain between populations and facilitates advances in neuroscience research. |
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## Usage |
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```python |
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from datasets import load_dataset |
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data = load_dataset("MuGemSt/AAL_statistics_volumn", split="train") |
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for item in data: |
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print(item) |
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``` |
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## Maintenance |
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```bash |
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git clone [email protected]:datasets/MuGemSt/AAL_statistics_volumn |
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cd AAL_statistics_volumn |
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``` |
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## Mirror |
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<https://www.modelscope.cn/datasets/MuGemSt/AAL_statistics_volumn> |
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## Reference |
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[1] [Chapter II ‐ Classifying AD patients and normal controls from brain images](https://github.com/MuGemSt/Medical_Image_Computing/wiki/Chapter-II-%E2%80%90-Classifying-AD-patients-and-normal-controls-from-brain-images) |
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