MungoMeng/Registration-NICE-Trans
[MICCAI2023] NICE-Trans: Non-iterative Coarse-to-fine Transformer Networks for Joint Affine and Deformable Image Registration
This project helps medical professionals and researchers precisely align medical images, such as MRI or CT scans, to compare them or integrate information. It takes two medical images and outputs a single, precisely aligned image, accommodating both large-scale repositioning and fine-grained shape adjustments. This is valuable for radiologists, neurologists, oncologists, or anyone analyzing changes or relationships between different scans.
No commits in the last 6 months.
Use this if you need a fast and accurate way to align different medical images, handling both overall positioning and detailed shape distortions simultaneously.
Not ideal if your primary need is general image manipulation outside of precise medical image alignment or if computational resources are severely limited for deep learning models.
Stars
27
Forks
5
Language
Python
License
GPL-3.0
Category
Last pushed
Mar 14, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/MungoMeng/Registration-NICE-Trans"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
voxelmorph/voxelmorph
Unsupervised Learning for Image Registration
uncbiag/uniGradICON
uniGradICON: A Foundation Model for Medical Image Registration (MICCAI 2024)
junyuchen245/TransMorph_Transformer_for_Medical_Image_Registration
TransMorph: Transformer for Unsupervised Medical Image Registration (PyTorch)
DeepRegNet/DeepReg
Medical image registration using deep learning
MLI-lab/DeepDeWedge
Self-supervised deep learning for denoising and missing wedge reconstruction of cryo-ET tomograms