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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Journal ArticleDOI
Atlas-based reconstruction of high performance brain MR data
TL;DR: A novel compressed sensing method which combines both external and internal information for the high-performance reconstruction of MRI data, and leverages the redundancy of nonlocal similar patches through a sparse representation model.
Journal ArticleDOI
A deep error correction network for compressed sensing MRI
TL;DR: The experimental results show the proposed DECN CS-MRI reconstruction framework can considerably improve upon existing inversion algorithms by supplementing with an error-correcting CNN, and validate the effectiveness and utility of the proposed framework.
Posted Content
Accelerated MRI Reconstruction with Separable and Enhanced Low-Rank Hankel Regularization
TL;DR: This work proposed to separably construct multiple small Hankel matrices from rows and columns of the k-space and then constrain the low-rankness on these small matrices and achieves the fastest computational speed in parameter imaging reconstruction.
Journal ArticleDOI
Registration-based image enhancement improves multi-atlas segmentation of the thalamic nuclei and hippocampal subfields.
Shunxing Bao,Camilo Bermudez,Yuankai Huo,Prasanna Parvathaneni,William Rodriguez,Susan M. Resnick,Pierre-François D'Haese,Maureen McHugo,Stephan Heckers,Benoit M. Dawant,Ilwoo Lyu,Bennett A. Landman +11 more
TL;DR: This work validate the usefulness and impact of BDRE for multi-atlas (MA) segmentation on two sets of structures of clinical interest and shows that BDRE can help MA segmentation for individual thalamic nuclei and hippocampal subfields.
Journal ArticleDOI
High quality and fast compressed sensing MRI reconstruction via edge-enhanced dual discriminator generative adversarial network
TL;DR: A novel edge-enhanced dual discriminator generative adversarial network architecture called EDDGAN for CSMRI reconstruction with high quality is proposed, which consistently outperforms state-of-the-art methods and obtains reconstructed images with rich edge details.
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.