Benchmarking deep learning-based low-dose CT image denoising algorithms.
Journal:
Medical physics
PMID:
39287517
Abstract
BACKGROUND: Long-lasting efforts have been made to reduce radiation dose and thus the potential radiation risk to the patient for computed tomography (CT) acquisitions without severe deterioration of image quality. To this end, various techniques have been employed over the years including iterative reconstruction methods and noise reduction algorithms.