Journal ArticleDOI
Image reconstruction of compressed sensing MRI using graph-based redundant wavelet transform.
TLDR
A graph-based redundant wavelet transform is introduced to sparsely represent magnetic resonance images in iterative image reconstructions and outperforms several state-of-the-art reconstruction methods in removing artifacts and achieves fewer reconstruction errors on the tested datasets.About:
This article is published in Medical Image Analysis.The article was published on 2016-01-01. It has received 150 citations till now. The article focuses on the topics: Iterative reconstruction & Wavelet transform.read more
Citations
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Proceedings ArticleDOI
A Novel Images Enhancement strategy Based on Dynamic Range Compression and Details Enhancement for MRI images
TL;DR: A new MRI images enhancement strategy is proposed which consists of a dynamic range compression (DRC) operation and a details enhancement (DE) operation which efficiently compress the high dynamic range to a suitable range and protect the difference between the pixels.
Journal ArticleDOI
Iterative self-consistent parallel magnetic resonance imaging reconstruction based on nonlocal low-rank regularization
TL;DR: In this article , a nonlocal low-rank (NLR)-SPIRiT model was proposed by incorporating NLR regularization into the iterative self-consistent parallel imaging reconstruction.
Proceedings ArticleDOI
Research on A Multi-slice MRI Reconstruction Algorithm Based on Deep Learning
TL;DR: In this paper , the DISN model engaged in network training through deep learning and carried out multi-slice reconstruction under different conditions through controlling the variables, and the experimental results showed that the effect of multiscale network reconstruction was always better than that of single-slice network reconstruction.
Journal ArticleDOI
PNCS: Pixel-Level Non-Local Method Based Compressed Sensing Undersampled MRI Image Reconstruction
Journal ArticleDOI
An Efficient Lightweight Generative Adversarial Network for Compressed Sensing Magnetic Resonance Imaging Reconstruction
TL;DR: Wang et al. as mentioned in this paper designed an efficient lightweight generative adversarial network (GAN) to achieve more accurate MRI reconstruction by using depthwise separable convolution as the basic component to reduce the number of learning parameters.
References
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Journal ArticleDOI
Image quality assessment: from error visibility to structural similarity
TL;DR: In this article, a structural similarity index is proposed for image quality assessment based on the degradation of structural information, which can be applied to both subjective ratings and objective methods on a database of images compressed with JPEG and JPEG2000.
Book
Introduction to Algorithms
TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
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$rm K$ -SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
TL;DR: A novel algorithm for adapting dictionaries in order to achieve sparse signal representations, the K-SVD algorithm, an iterative method that alternates between sparse coding of the examples based on the current dictionary and a process of updating the dictionary atoms to better fit the data.
Journal ArticleDOI
An Iterative Thresholding Algorithm for Linear Inverse Problems with a Sparsity Constraint
TL;DR: It is proved that replacing the usual quadratic regularizing penalties by weighted 𝓁p‐penalized penalties on the coefficients of such expansions, with 1 ≤ p ≤ 2, still regularizes the problem.