Advancing Low-Rank and Local Low-Rank Matrix Approximation in Medical Imaging: A Systematic Literature Review and Future Directions
The large volume and complexity of medical imaging datasets are bottlenecks for storage,
transmission, and processing. To tackle these challenges, the application of low-rank matrix …
transmission, and processing. To tackle these challenges, the application of low-rank matrix …
Spatio-temporal signal recovery based on low rank and differential smoothness
The analysis of spatio-temporal signals plays an important role in various fields including
sociology, climatology, and environmental studies, etc. Due to the abrupt breakdown of the …
sociology, climatology, and environmental studies, etc. Due to the abrupt breakdown of the …
[HTML][HTML] Designing contrasts for rapid, simultaneous parameter quantification and flow visualization with quantitative transient-state imaging
Magnetic resonance imaging (MRI) has evolved into an outstandingly versatile diagnostic
modality, as it has the ability to non-invasively produce detailed information on a tissue's …
modality, as it has the ability to non-invasively produce detailed information on a tissue's …
[HTML][HTML] Design of microwave-based brain tumor detection framework with the development of sparse and low-rank compressive sensing image reconstruction
HR Sholeh, M Rizkinia, B Basari - International Journal of …, 2020 - ijtech.eng.ui.ac.id
Design of Microwave-based Brain Tumor Detection Framework with the Development of
Sparse and Low-Rank Compressive Sensing Image Reconstruction title Title Author Issue …
Sparse and Low-Rank Compressive Sensing Image Reconstruction title Title Author Issue …
Robust Depth Linear Error Decomposition with Double Total Variation and Nuclear Norm for Dynamic MRI Reconstruction
Compressed Sensing (CS) significantly speeds up Magnetic Resonance Image (MRI)
processing and achieves accurate MRI reconstruction from under-sampled k-space data …
processing and achieves accurate MRI reconstruction from under-sampled k-space data …
Accelerating Dynamic MRI Reconstruction Using Adaptive Sequentially Truncated Higher-Order Singular Value Decomposition
Y Li, Q Shen, M Jiang, L Zhu, Y Li… - Current Medical …, 2022 - ingentaconnect.com
Background: Dynamic magnetic resonance imaging (dMRI) plays an important role in
cardiac perfusion and functional clinical exams. However, further applications are limited by …
cardiac perfusion and functional clinical exams. However, further applications are limited by …
[HTML][HTML] 基于多尺度低秩的心脏磁共振图像的高质量重构算法
阳衡， 峰陈， 剑锋徐， 敏汤 - Sheng Wu Yi Xue Gong Cheng Xue Za …, 2019 - ncbi.nlm.nih.gov
借助信号内在的稀疏性或可压缩性， 压缩感知利用随机投影实现以远低于奈奎斯特频率的采样
频率下对压缩后数据的采集。 结合压缩感知和低秩思想， 可以加快心脏磁共振（ CMR） …
频率下对压缩后数据的采集。 结合压缩感知和低秩思想， 可以加快心脏磁共振（ CMR） …
[PDF][PDF] A Robust Reconstruction Method for Quantitative Perfusion MRI: Application to Brain Dynamic Susceptibility Contrast (DSC) Imaging
We propose a robust reconstruction model for dynamic perfusion magnetic resonance
imaging (MRI) from undersampled k-space data. Our method is based on a joint …
imaging (MRI) from undersampled k-space data. Our method is based on a joint …
Robust reconstruction of accelerated perfusion MRI using local and nonlocal constraints
Dynamic perfusion magnetic resonance (MR) imaging is a commonly used imaging
technique that allows to measure the tissue perfusion in an organ of interest via assessment …
technique that allows to measure the tissue perfusion in an organ of interest via assessment …
Advanced reconstruction techniques in perfusion magnetic resonance imaging
C Ulas - 2021 - mediatum.ub.tum.de
Perfusion magnetic resonance imaging (MRI), as being one of the most crucial and
promising dynamic MRI modality, enables the quantification of perfusion related parameters …
promising dynamic MRI modality, enables the quantification of perfusion related parameters …