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Reconstruction techniques for cardiac cine MRI
The present survey describes the state-of-the-art techniques for dynamic cardiac magnetic
resonance image reconstruction. Additionally, clinical relevance, main challenges, and …
resonance image reconstruction. Additionally, clinical relevance, main challenges, and …
Deep learning for fast and spatially constrained tissue quantification from highly accelerated data in magnetic resonance fingerprinting
Magnetic resonance fingerprinting (MRF) is a quantitative imaging technique that can
simultaneously measure multiple important tissue properties of human body. Although MRF …
simultaneously measure multiple important tissue properties of human body. Although MRF …
Clinical feasibility of deep learning reconstruction in liver diffusion-weighted imaging: Improvement of image quality and impact on apparent diffusion coefficient value
Q Chen, S Fang, Y Yuchen, R Li, R Deng… - European journal of …, 2023 - Elsevier
Purpose Diffusion-weighted imaging (DWI) of the liver suffers from low resolution, noise, and
artifacts. This study aimed to investigate the effect of deep learning reconstruction (DLR) on …
artifacts. This study aimed to investigate the effect of deep learning reconstruction (DLR) on …
Manifold learning via linear tangent space alignment (LTSA) for accelerated dynamic MRI with sparse sampling
The spatial resolution and temporal frame-rate of dynamic magnetic resonance imaging
(MRI) can be improved by reconstructing images from sparsely sampled-space data with …
(MRI) can be improved by reconstructing images from sparsely sampled-space data with …
Manifold recovery using kernel low-rank regularization: Application to dynamic imaging
In this paper, we introduce a novel kernel low-rank algorithm to recover free-breathing and
ungated dynamic MRI data from highly undersampled measurements. The image frames in …
ungated dynamic MRI data from highly undersampled measurements. The image frames in …
OFx: A method of 4D image construction from free-breathing non-gated MRI slice acquisitions of the thorax via optical flux
Purpose Since real-time 4D dynamic magnetic resonance imaging (dMRI) methods with
adequate spatial and temporal resolution for imaging the pediatric thorax are currently not …
adequate spatial and temporal resolution for imaging the pediatric thorax are currently not …
Deep learning-based ECG-free cardiac navigation for multi-dimensional and motion-resolved continuous magnetic resonance imaging
For the clinical assessment of cardiac vitality, time-continuous tomographic imaging of the
heart is used. To further detect eg, pathological tissue, multiple imaging contrasts enable a …
heart is used. To further detect eg, pathological tissue, multiple imaging contrasts enable a …
Manifold‐based respiratory phase estimation enables motion and distortion correction of free‐breathing cardiac diffusion tensor MRI
Purpose For in vivo cardiac DTI, breathing motion and B0 field inhomogeneities produce
misalignment and geometric distortion in diffusion‐weighted (DW) images acquired with …
misalignment and geometric distortion in diffusion‐weighted (DW) images acquired with …
Embedding-Alignment Fusion-Based Graph Convolution Network With Mixed Learning Strategy for 4D Medical Image Reconstruction
In recent years, 4D medical image involving structural and motion information of tissue has
attracted increasing attention. The key to the 4D image reconstruction is to stack the 2D …
attracted increasing attention. The key to the 4D image reconstruction is to stack the 2D …
Multilinear kernel regression and imputation via manifold learning
This paper introduces a novel kernel regression framework for data imputation, coined
multilinear kernel regression and imputation via the manifold assumption (MultiL-KRIM) …
multilinear kernel regression and imputation via the manifold assumption (MultiL-KRIM) …