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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Journal ArticleDOI
Patient-attentive sequential strategy for perimetry-based visual field acquisition
TL;DR: PASS is introduced, a novel perimetry testing strategy that requires fewer locations in order to effectively estimate 2D visual fields, and outperforms state‐of‐the‐art methods, leading to more accurate reconstructions while reducing between 30% and 70% the duration of the patient examination.
Journal ArticleDOI
Adaptive thresholding HOSVD with rearrangement of tensors for image denoising
TL;DR: This paper proposes an adaptive thresholding HOSVD with rearrangement of tensors, called ATH-HOSVD, which considers the spatial distribution of elements in the core tensors and adopts the indices of transform coefficients to produce adaptive threshold.
Journal ArticleDOI
Multilevel wavelet-based hierarchical networks for image compressed sensing
TL;DR: Wang et al. as discussed by the authors proposed a multilevel wavelet-based hierarchical networks for image compressed sensing (dubbed MWHCS-Net), which consists of three modules: a sampling module based on a multi-level wavelet transform, a hierarchical initial reconstruction module and a lightweight deep reconstruction module.
Journal ArticleDOI
Multi-wavelet level comparison on compressive sensing for MRI image reconstruction
TL;DR: The experimental results showed that the use of wavelet multi-level can generate higher compression ratio but requires a longer processing time, and that the higher the level of decomposition in wavelets, the value of both decreases.
Journal ArticleDOI
Orthogonal tensor dictionary learning for accelerated dynamic MRI.
TL;DR: Numerical experiments on phantom and synthetic data show significant improvements in reconstruction accuracy and computational efficiency obtained by the proposed scheme over the existing method that uses the 1D/2D model with overcomplete dictionary learning.
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.
Journal ArticleDOI
$rm K$ -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.