Magnetic resonance imaging (MRI) Diffusion MRI (dMRI)Super resolution Generative adversarial networks (GANs)Spatial resolution is one of the main constraints in diffusion Magnetic Resonance Imaging (dMRI). Increasing resolution leads to a decrease in SNR of the diffusion images. Acquiring high ...
To solve the problem of long sampling time for diffusion magnetic resonance imaging (dMRI), in this study we propose a dMRI super-resolution reconstruction network. This method not only uses a three-dimensional (3D) convolution kernel to reconstruct the dMRI data in the space and angle domains...
The hippocampus is a key component of emotional and memory circuits and is broadly connected throughout the brain. We tracked the whole-brain connections of white matter fibres from the hippocampus using ultra-high angular resolution diffusion MRI in both a single 1150-direction dataset and a large...
Super-resolution reconstruction Diffusion magnetic resonance imaging Tensor-valued diffusion encoding Ultra-high b-values Rectified noise floor Noise propagation 1. Introduction Diffusion MRI (dMRI) is a non-invasive method for investigating tissue microstructure in healthy and pathological tissue. Investigatio...
To address this challenge, we propose a self-supervised arbitrary scale super-angular resolution diffusion MRI reconstruction network (SARDI-nn), which can generate DW images along any directions from few acquisitions, allowing to overcome the limits of diffusion direction number on exploring the tissue...
3.5 Image Super-Resolution Saharia 等人,[18]将扩散模型应用于超分辨率。他们的反向过程学会了基于低分辨率版本生成的高质量图像。这项工作采用了在[2]、[6]和以下数据集中提供的体系结构: CelebA-HQ、FFHQ和ImageNet。丹尼尔斯等人。[25]使用基于分数的模型从两个分布的辛克霍恩耦合中进行抽样。他们的方法用神经...
33、Text-guided Explorable Image Super-resolution 本文介绍零样本文本引导的开放域图像超分辨率解决方案的问题。目标是允许用户在不明确训练这些特定退化的情况下,探索各种保持与低分辨率输入一致的、语义准确的重建结果。 提出两种零样本文本引导超分辨率的方法,一种是修改文本到图像(T2I)扩散模型的生成过程,以促进与低...
Since the prevalence of such complex brain areas is estimated to 60 to 90% of the white matter, at the current imaging resolution (~1 mm3), MIX will enable the neuroimaging community to investigate the microstructure of the brain white matter in ways which are currently not possible. We ...
Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolution 文章解读:http://www.studyai.com/xueshu/paper/detail/1fd6ad35fb 文章链接:(https://openaccess.thecvf.com/content/CVPR2024/html/Li_Rethinking_Diffusion_Model_for_Multi-Contrast_MRI_Super-Resolution_CVPR_2024_paper.html) ...
Tanno, R., et al.: Bayesian image quality transfer with CNNs: exploring uncertainty in dMRI super-resolution. In: Descoteaux, M., Maier-Hein, L., Franz, A., Jannin, P., Collins, D.L., Duchesne, S. (eds.) MICCAI 2017. LNCS, vol. 10433, pp. 611–619. Springer, Cham (2017)...