LemuelPuglisi/BrLP
[MICCAI, 2024] (Oral, RU @ MedIA Best Paper Award) Official implementation of the Brain Latent Progression (BrLP) method from "Enhancing Spatiotemporal Disease Progression Models via Latent Diffusion and Prior Knowledge"
Combines a variational autoencoder, diffusion-based UNet, and ControlNet architecture to model individual spatiotemporal brain disease progression from longitudinal 3D MRI scans in latent space. Integrates prior knowledge through auxiliary disease progression models (e.g., DCM) via ControlNet conditioning, enabling personalized trajectory prediction while reducing computational overhead. Provides a CLI tool with optional automatic brain segmentation via SynthSeg and inference through YAML configuration, built on MONAI's GenerativeModels framework.
122 stars.
Stars
122
Forks
9
Language
Python
License
MIT
Category
Last pushed
Oct 31, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/LemuelPuglisi/BrLP"
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...
GabrieleLozupone/LDAE
Official PyTorch implementation of "Latent Diffusion Autoencoders: Toward Efficient and...
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
sandialabs/pvcracks
Si-PV cell crack image recognition, modeling, and power loss prediction