Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review
Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …
the health and well-being of millions of people worldwide. Structural and functional …
Emerging trends in fast MRI using deep-learning reconstruction on undersampled k-space data: a systematic review
Magnetic Resonance Imaging (MRI) is an essential medical imaging modality that provides
excellent soft-tissue contrast and high-resolution images of the human body, allowing us to …
excellent soft-tissue contrast and high-resolution images of the human body, allowing us to …
Adaptive diffusion priors for accelerated MRI reconstruction
Deep MRI reconstruction is commonly performed with conditional models that de-alias
undersampled acquisitions to recover images consistent with fully-sampled data. Since …
undersampled acquisitions to recover images consistent with fully-sampled data. Since …
Joint cross-attention network with deep modality prior for fast MRI reconstruction
Current deep learning-based reconstruction models for accelerated multi-coil magnetic
resonance imaging (MRI) mainly focus on subsampled k-space data of single modality using …
resonance imaging (MRI) mainly focus on subsampled k-space data of single modality using …
Adaptive channel-modulated personalized federated learning for magnetic resonance image reconstruction
Magnetic resonance imaging (MRI) is extensively utilized in clinical practice for diagnostic
purposes, owing to its non-invasive nature and remarkable ability to provide detailed …
purposes, owing to its non-invasive nature and remarkable ability to provide detailed …
Joint optimization of Cartesian sampling patterns and reconstruction for single‐contrast and multi‐contrast fast magnetic resonance imaging
Background and objective Compressed sensing (CS) has gained increased attention in
magnetic resonance imaging (MRI), leveraging its efficacy to accelerate image acquisition …
magnetic resonance imaging (MRI), leveraging its efficacy to accelerate image acquisition …
Deep unfolding network with spatial alignment for multi-modal mri reconstruction
Abstract Multi-modal Magnetic Resonance Imaging (MRI) offers complementary diagnostic
information, but some modalities are limited by the long scanning time. To accelerate the …
information, but some modalities are limited by the long scanning time. To accelerate the …
[PDF][PDF] 磁共振成像人工智能的研究现状及发展前景
王梅云 - 磁共振成像, 2023 - med-sci.cn
随着MRI 技术的迅速发展, 更加先进的高性能MRI 设备的临床投用, 以及各种图像后处理软件
不断开发, 不仅MRI 性能和图像质量得到了提高, 更重要的是使原来难以发现的组织结构和器官 …
不断开发, 不仅MRI 性能和图像质量得到了提高, 更重要的是使原来难以发现的组织结构和器官 …
Multi-Contrast Complementary Learning for Accelerated MR Imaging
Thanks to its powerful ability to depict high-resolution anatomical information, magnetic
resonance imaging (MRI) has become an essential non-invasive scanning technique in …
resonance imaging (MRI) has become an essential non-invasive scanning technique in …
Fast multi-contrast MRI acquisition by optimal sampling of information complementary to pre-acquired MRI contrast
Recent studies on multi-contrast MRI reconstruction have demonstrated the potential of
further accelerating MRI acquisition by exploiting correlation between contrasts. Most of the …
further accelerating MRI acquisition by exploiting correlation between contrasts. Most of the …