Image distortion correction for MRI in low field permanent magnet systems with strong B0 inhomogeneity and gradient field nonlinearities
Autor: | Kirsten Koolstra, Andrew G. Webb, Thomas O'Reilly, Peter Börnert |
---|---|
Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Image quality
Short Communication Fast Fourier transform Biophysics Iterative reconstruction 030218 nuclear medicine & medical imaging Tikhonov regularization 03 medical and health sciences symbols.namesake B-0 mapping Distortion correction 0302 clinical medicine Image Processing Computer-Assisted Radiology Nuclear Medicine and imaging Computer Simulation Model-based reconstruction Physics Radiological and Ultrasound Technology Fourier Analysis Phantoms Imaging Image (category theory) Conjugate phase reconstruction Mathematical analysis Order (ring theory) Magnetic Resonance Imaging Low field MRI Compressed sensing Fourier transform B0 mapping symbols Magnets 030217 neurology & neurosurgery Algorithms |
Zdroj: | Magma (New York, N.y.) Magnetic Resonance Materials in Physics, Biology and Medicine, 34, 631-642. SPRINGER Magnetic Resonance Materials in Physics, Biology and Medicine |
ISSN: | 1352-8661 0968-5243 |
Popis: | Objective To correct for image distortions produced by standard Fourier reconstruction techniques on low field permanent magnet MRI systems with strong $${B}_{0}$$ B 0 inhomogeneity and gradient field nonlinearities. Materials and methods Conventional image distortion correction algorithms require accurate $${\Delta B}_{0}$$ Δ B 0 maps which are not possible to acquire directly when the $${B}_{0}$$ B 0 inhomogeneities also produce significant image distortions. Here we use a readout gradient time-shift in a TSE sequence to encode the $${B}_{0}$$ B 0 field inhomogeneities in the k-space signals. Using a non-shifted and a shifted acquisition as input, $$\Delta {B}_{0}$$ Δ B 0 maps and images were reconstructed in an iterative manner. In each iteration, $$\Delta {B}_{0}$$ Δ B 0 maps were reconstructed from the phase difference using Tikhonov regularization, while images were reconstructed using either conjugate phase reconstruction (CPR) or model-based (MB) image reconstruction, taking the reconstructed field map into account. MB reconstructions were, furthermore, combined with compressed sensing (CS) to show the flexibility of this approach towards undersampling. These methods were compared to the standard fast Fourier transform (FFT) image reconstruction approach in simulations and measurements. Distortions due to gradient nonlinearities were corrected in CPR and MB using simulated gradient maps. Results Simulation results show that for moderate field inhomogeneities and gradient nonlinearities, $$\Delta {B}_{0}$$ Δ B 0 maps and images reconstructed using iterative CPR result in comparable quality to that for iterative MB reconstructions. However, for stronger inhomogeneities, iterative MB reconstruction outperforms iterative CPR in terms of signal intensity correction. Combining MB with CS, similar image and $$\Delta {B}_{0}$$ Δ B 0 map quality can be obtained without a scan time penalty. These findings were confirmed by experimental results. Discussion In case of $${B}_{0}$$ B 0 inhomogeneities in the order of kHz, iterative MB reconstructions can help to improve both image quality and $$\Delta {B}_{0}$$ Δ B 0 map estimation. |
Databáze: | OpenAIRE |
Externí odkaz: |