AIM-KannLab/pediatric-brain-age
Code for paper "Diffusion Deep Learning for Brain Age Prediction and Longitudinal Tracking in Children through Adulthood
This project helps researchers analyze T1-weighted MRI brain scans of children and adolescents to predict brain age. You input a T1-weighted MRI scan, and it outputs a predicted brain age, which can then be tracked over time. This tool is designed for neuroscientists, developmental biologists, and clinical researchers studying brain development.
No commits in the last 6 months.
Use this if you need an advanced, accurate method to estimate brain age from T1-weighted MRI scans in pediatric populations for research purposes.
Not ideal if you are looking for a tool for clinical diagnosis or if you lack access to high-performance computing with a GPU.
Stars
10
Forks
1
Language
Python
License
—
Category
Last pushed
Apr 16, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/AIM-KannLab/pediatric-brain-age"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
ge-xing/Diff-UNet
Diff-UNet: A Diffusion Embedded Network for Volumetric Segmentation. (using diffusion for 3D...
LemuelPuglisi/BrLP
[MICCAI, 2024] (Oral, RU @ MedIA Best Paper Award) Official implementation of the Brain Latent...
Warvito/generative_chestxray
Repository to train Latent Diffusion Models on Chest X-ray data (MIMIC-CXR) using MONAI...
jwmao1/MedSegFactory
[ICCV 2025] MedSegFactory: Text-Guided Generation of Medical Image-Mask Pairs
GabrieleLozupone/LDAE
Official PyTorch implementation of "Latent Diffusion Autoencoders: Toward Efficient and...