Dual-branch residual encoder-decoder convolutional neural network (DB-REDCNN): a computed tomography-integrated multimodal network for positron emission tomography denoising

The proposed DB-REDCNN model, by integrating structural priors from CT through a multibranch architecture, enhances the synthesis of FDPET from LDPET. It achieves superior quantitative performance, improves edge sharpness in lesion regions, and preserves peak SUV information, thereby offering a clinically valuable approach for radiation dose reduction in PET imaging.