Journal ArticleDOI
Image reconstruction of compressed sensing MRI using graph-based redundant wavelet transform.
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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
Deep Residual-ASPP Generative Adversarial Network for CS-MRI Reconstruction
TL;DR: In this paper, a new GAN-based deep learning method called RAGAN is proposed for MRI reconstruction, which combines residual-ASPP blocks and the gradient information guided loss for better reconstruction effect of texture and detailed information at different scales.
Journal ArticleDOI
Discrete Shearlets as a Sparsifying Transform in Low-Rank Plus Sparse Decomposition for Undersampled (k, t)-Space MR Data
TL;DR: L+S decomposition, using discrete shearlets as sparsifying transforms, successfully separated the low-rank (background and periodic motion) from the sparse component (enhancement or bowel motility) for both DCE and small bowel data.
Journal ArticleDOI
Compressive Sensing MRI Reconstruction with Shearlet Sparsity and non-Convex Hybrid Total Variation
Nikhil Dhengre,Saugata Sinha +1 more
Proceedings Article
Active Deep Probabilistic Subsampling
TL;DR: Active-DPS as discussed by the authors generalizes Deep Probabilistic Subsampling (DPS) to a sequential method that actively picks the next sample based on the information acquired so far.
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.