Landlocked 发表于 2025-3-23 13:03:52
Efficient Image Registration Network for Non-Rigid Cardiac Motion Estimationrdiac CINE MRIs indicate that the proposed method outperforms the competing approaches substantially, with more than 25% reduction in residual photometric error, and up to 100. faster inference speed compared to conventional methods.nitroglycerin 发表于 2025-3-23 16:23:33
http://reply.papertrans.cn/63/6207/620631/620631_12.pngMUTE 发表于 2025-3-23 18:04:31
http://reply.papertrans.cn/63/6207/620631/620631_13.pngRALES 发表于 2025-3-24 01:49:19
Real-Time Video Denoising to Reduce Ionizing Radiation Exposure in Fluoroscopic Imagingoom monitor. On the other hand, we present a video denoising method which executes orders of magnitude faster while achieving state-of-the-art performance. This provides compelling potential for real-time clinical application in fluoroscopic imaging.Middle-Ear 发表于 2025-3-24 02:57:03
http://reply.papertrans.cn/63/6207/620631/620631_15.pngBYRE 发表于 2025-3-24 07:01:23
Deep MRI Reconstruction with Generative Vision Transformerstention vision transformers. Cross-attention mechanism between latents and image features serve to enhance representational learning of local and global context. Meanwhile, latent and noise injections at each network layer permit fine control of generated image features, improving model invertibilit影响 发表于 2025-3-24 11:34:19
Distortion Removal and Deblurring of Single-Shot DWI MRI Scanse of deblurred EPI-DWI images for performing accurate medical diagnosis and multi parametric longitudinal analysis in brain tumors. We use data augmentation, dilated convolution, and ELU (exponential linear unit) to design a suitable architecture that achieves superior performance in terms of accuraProject 发表于 2025-3-24 18:12:51
http://reply.papertrans.cn/63/6207/620631/620631_18.pngmastoid-bone 发表于 2025-3-24 21:26:02
http://reply.papertrans.cn/63/6207/620631/620631_19.png感情 发表于 2025-3-25 01:39:23
A Frequency Domain Constraint for Synthetic and Real X-ray Image Super Resolutionain loss as a constraint to further improve the quality of the RefSR results with fine details and without obvious artifacts. To the best of our knowledge, this is the first paper utilizing the frequency domain for the loss functions in the field of super-resolution. We achieved good results in eval