figures

📝 Jupyter Notebooks for Figure & Table Reproduction

This repository provides Jupyter notebooks for recreating all figures and tables used in the project.
Each notebook has specific input requirements, detailed below.

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Data Requirements

• Subject metadata csv
  Must include subject IDs, demographics, and additional fields depending on the notebook (e.g., age information, country). for detailed template of subject metadata csv: subject csv

• Additional imaging data (for resection mapping)

  • MNI-registered resection cavity masks
  • MNI template
  • MNI brain mask

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01_Fig_age_distribution.ipynb

Requirements:

• The master CSV file must contain:
  • age_at_surgery, or
  • age_at_preop_scan
• The script prioritizes age at surgery. If missing, it uses age at preoperative scan.
• The notebook reports the number of subjects missing both pieces of information.

Output:

• Age distribution plot
• Pediatric subjects (age < 18) plotted in orange
• Adult subjects (age ≥ 18) plotted in blue

Example:

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02_Fig_site_worldmap.ipynb

Requirements:

• The master CSV file must include the country corresponding to each contributing site.

Output:

• A world map illustrating the geographic distribution of contributing sites.

Example:

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03_Fig_resection_distribution.ipynb

Requirements:

• MNI-registered resection cavity masks
• MNI template
• MNI brain mask

Functionality:

• Resection masks are mapped onto MNI space.
• A density map is created with a maximum threshold of 25.
• Transparent background with colour bar
• A total of 60 PNG images are generated:
  • 3 anatomical planes (sagittal, coronal, axial)
  • 20 slices per plane

Example: