言外之意 发表于 2025-3-30 09:12:46
An Explainable Deep Framework: Towards Task-Specific Fusion for Multi-to-One MRI Synthesisvarious reasons. To address this issue, MRI synthesis is a potential solution. Recent deep learning-based methods have achieved good performance in combining multiple available sequences for missing sequence synthesis. Despite their success, these methods lack the ability to quantify the contributioPetechiae 发表于 2025-3-30 13:23:14
Structure-Preserving Synthesis: MaskGAN for Unpaired MR-CT Translation they often generate inaccurate mappings that shift the anatomy. This problem is further exacerbated when the images from the source and target modalities are heavily misaligned. Recently, current methods have aimed to address this issue by incorporating a supplementary segmentation network. UnfortuBph773 发表于 2025-3-30 17:32:21
Alias-Free Co-modulated Network for Cross-Modality Synthesis and Super-Resolution of MR Imagesed modality images and reduce slice thickness for magnetic resonance imaging (MRI), respectively. It is also desirable to build a network for simultaneous cross-modality and super-resolution (CMSR) so as to further bridge the gap between clinical scenarios and research studies. However, these works揭穿真相 发表于 2025-3-30 23:48:20
Multi-perspective Adaptive Iteration Network for Metal Artifact Reductionality of metal-corrupted image remains a challenge. Although the deep learning-based MAR methods have achieved impressive success, their interpretability and generalizability need further improvement. It is found that metal artifacts mainly concentrate in high frequency, and their distributions in t压迫 发表于 2025-3-31 01:32:56
http://reply.papertrans.cn/63/6293/629220/629220_55.pngTinea-Capitis 发表于 2025-3-31 07:07:09
Low-Dose CT Image Super-Resolution Network with Dual-Guidance Feature Distillation and Dual-Path Cons have been proposed to deal with those issues, but there still exists drawbacks: (1) convolution without guidance causes essential information not highlighted; (2) features with fixed-resolution lose the attention to multi-scale information; (3) single super-resolution module fails to balance detaiCHARM 发表于 2025-3-31 10:34:52
http://reply.papertrans.cn/63/6293/629220/629220_57.png歪曲道理 发表于 2025-3-31 14:19:35
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http://reply.papertrans.cn/63/6293/629220/629220_59.pngSelf-Help-Group 发表于 2025-3-31 23:07:31
Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesisobustness, domain transfer, causal modelling, and operator training become approachable through synthetic data. Especially, heavily operator-dependant modalities like Ultrasound imaging require robust frameworks for image and video generation. So far, video generation has only been possible by provi