The aim is to develop a low-dose CT image denoising framework that is both interpretable and user-controlled.
Developed the Filter2Noise (F2N) framework for image denoising.
Evaluated performance across different CT scanners and imaging protocols.
Ensured the framework requires no retraining for different environments.
Achieved competitive denoising performance.
Maintained complete interpretability of the denoising process.
Enabled user control for radiologists in adjusting parameters.
Abstract
F2N reconciles competitive performance with complete interpretability and user control, providing radiologists with a verifiable tool that works across scanners and protocols without retraining.