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research-article

Dependent nonparametric bayesian group dictionary learning for online reconstruction of dynamic MR images

Authors:

Dornoosh Zonoobi,

Shahrooz F. Roohi,

Ashraf A. Kassim,

Jacob L. JaremkoAuthors Info & Claims

Volume 63, Issue C

Pages 518 - 530

https://doi.org/10.1016/j.patcog.2016.09.038

Published: 01 March 2017 Publication History

Abstract

In this paper, we introduce a dictionary learning based approach applied to the problem of real-time reconstruction of MR image sequences that are highly undersampled in k-space. Unlike traditional dictionary learning, our method integrates both global and patch-wise (local) sparsity information and incorporates some priori information into the reconstruction process. Moreover, we use a Dependent Hierarchical Beta-process as the prior for the group-based dictionary learning, which adaptively infers the dictionary size and the sparsity of each patch; and also ensures that similar patches are manifested in terms of similar dictionary atoms. An efficient numerical algorithm based on the alternating direction method of multipliers (ADMM) is also presented. Through extensive experimental results we show that our proposed method achieves superior reconstruction quality, compared to the other state-of-the- art DL-based methods.

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Highlights

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A novel dictionary learning-based algorithm for online reconstruction of dynamic MR images is proposed.

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The algorithm consists of both patch-based (local) and global sparsity terms.

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The group patching is employed to classify the patches based on their similarities.

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A modified dependent hierarchical beta process (dHBP) is utilized as the prior for the dictionary learning process.

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Cited By

Sun YChen JLiu QLiu G(2020)Learning image compressed sensing with sub-pixel convolutional generative adversarial networkPattern Recognition10.1016/j.patcog.2019.10705198:COnline publication date: 1-Feb-2020
https://dl.acm.org/doi/10.1016/j.patcog.2019.107051

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Dependent nonparametric bayesian group dictionary learning for online reconstruction of dynamic MR images

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Information

Published In

cover image Pattern Recognition

Pattern Recognition Volume 63, Issue C

Mar 2017

740 pages

ISSN:0031-3203

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Elsevier Ltd.

Publisher

Elsevier Science Inc.

United States

Publication History

Published: 01 March 2017

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Cited By

Sun YChen JLiu QLiu G(2020)Learning image compressed sensing with sub-pixel convolutional generative adversarial networkPattern Recognition10.1016/j.patcog.2019.10705198:COnline publication date: 1-Feb-2020
https://dl.acm.org/doi/10.1016/j.patcog.2019.107051

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