Comparative Study of Training Strategies for Projection-Domain Denoising in Multislice Helical CT.
This study compared the performance of various deep learning-based denoising models applied to 2D cone-beam CT projections and highlighted the importance of physical modeling, data consistency, and the training strategy of deep learning-based algorithms for robust, generalizable LDCT denoising.