ADAPTIVE STRUCTURED LOW RANK ALGORITHM FOR MR IMAGE RECOVERY

We introduce an adaptive structured low rank algorithm to recover MR images from their undersampled Fourier coefficients. The image is modeled as a combination of a piecewise constant component and a piecewise linear component. The Fourier coefficients of each component satisfy an annihilation relation, which results in a structured Toeplitz matrix. We exploit the low rank property of the matrices to formulate a combined regularized optimization problem, which can be solved efficiently. Numerical experiments indicate that the proposed algorithm provides improved recovery performance over the previously proposed algorithms.

Medienart:

E-Artikel

Erscheinungsjahr:

2018

Erschienen:

2018

Enthalten in:

Zur Gesamtaufnahme - volume:2018

Enthalten in:

Proceedings. IEEE International Symposium on Biomedical Imaging - 2018(2018) vom: 01. Apr., Seite 1260-1263

Sprache:

Englisch

Beteiligte Personen:

Hu, Yue [VerfasserIn]
Liu, Xiaohan [VerfasserIn]
Jacob, Mathews [VerfasserIn]

Links:

Volltext

Themen:

Compressed sensing
Journal Article
MRI reconstruction
Structured low rank matrix

Anmerkungen:

Date Revised 26.02.2021

published: Print-Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.1109/isbi.2018.8363800

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM321819659