eeulig/ldct-benchmark
A benchmark for deep learning-based low dose CT image denoising
This project helps medical physicists and radiologists improve the quality of low-dose CT (LDCT) scans. It takes noisy LDCT images and applies advanced denoising algorithms to produce clearer, more diagnostically valuable images. This is for researchers and practitioners working to reduce radiation exposure in CT imaging while maintaining image clarity.
No commits in the last 6 months. Available on PyPI.
Use this if you need to fairly compare different deep learning algorithms for denoising low-dose CT images or want to apply pre-trained, optimized models to improve your own LDCT scans.
Not ideal if you are looking for a general-purpose image denoising tool for non-medical images or if you need to denoise CT images from modalities other than low-dose.
Stars
39
Forks
5
Language
Python
License
MIT
Category
Last pushed
Apr 15, 2025
Commits (30d)
0
Dependencies
12
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