Browsing by Subject "Balanced SSFP"

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Open Access
Constrained ellipse fitting for efficient parameter mapping with phase-cycled bSSFP MRI
(IEEE, 2021-08-05) Keskin, K.; Yılmaz, Uğur; Çukur, Tolga
Balanced steady-state free precession (bSSFP) imaging enables high scan efficiency in MRI, but differs from conventional sequences in terms of elevated sensitivity to main field inhomogeneity and nonstandard T2/T1 -weighted tissue contrast. To address these limitations, multiple bSSFP images of the same anatomy are commonly acquired with a set of different RF phase-cycling increments. Joint processing of phase-cycled acquisitions serves to mitigate sensitivity to field inhomogeneity. Recently phase-cycled bSSFP acquisitions were also leveraged to estimate relaxation parameters based on explicit signal models. While effective, these model-based methods often involve a large number of acquisitions (N ≈ 10-16), degrading scan efficiency. Here, we propose a new constrained ellipse fitting method (CELF) for parameter estimation with improved efficiency and accuracy in phase-cycled bSSFP MRI. CELF is based on the elliptical signal model framework for complex bSSFP signals; and it introduces geometrical constraints on ellipse properties to improve estimation efficiency, and dictionary-based identification to improve estimation accuracy. CELF generates maps of T1 , T2 , off-resonance and on-resonant bSSFP signal by employing a separate B1 map to mitigate sensitivity to flip angle variations. Our results indicate that CELF can produce accurate off-resonance and banding-free bSSFP maps with as few as N = 4 acquisitions, while estimation accuracy for relaxation parameters is notably limited by biases from microstructural sensitivity of bSSFP imaging.
Open Access
Efficient parameter mapping for magnetic resonance imaging
(2019-07) Keskin, Kübra
Balanced steady-state free precession (bSSFP) is a magnetic resonance imaging (MRI) sequence that enables high signal-to-noise ratios in short scan times. However, it has elevated sensitivity to main eld inhomogeneity, which leads to banding artifacts near regions of relatively large o -resonance shifts. To suppress these artifacts, multiple bSSFP images of the same anatomy are commonly acquired with a set of di erent RF phase-cycling increments. Joint processing of phase-cycled acquisitions has long been employed to eliminate banding artifacts due to eld inhomogeneity. Multiple bSSFP acquisitions can be further used for parameter mapping by exploiting the signal model of phase-cycled bSSFP. While model based approaches for mapping are e ective, they often need a large number of acquisitions, inherently limiting scan e ciency. In this thesis, we propose a new method for parameter mapping with improved e ciency and accuracy in phasecycled bSSFP MRI. The proposed method is based on the elliptical signal model framework for complex bSSFP signals; and introduces an observation about the signal's geometry to the constrained parameter mapping problem, such that the number of unknowns and thereby the required number of acquisitions can be reduced. It also leverages dictionary-based identi cation to improve estimation accuracy. Simulated, phantom and in vivo experiments demonstrate that the proposed method enables improved parameter mapping with fewer acquisitions.
Open Access
Factorized sensitivity estimation for artifact suppression in phase‐cycled bSSFP MRI
(Wiley, 2020) Bıyık, Erdem; Keskin, Kübra; Dar, Salman Ul Hassan; Koç, Aykut; Çukur, Tolga
Objective: Balanced steady‐state free precession (bSSFP) imaging suffers from banding artifacts in the presence of magnetic field inhomogeneity. The purpose of this study is to identify an efficient strategy to reconstruct banding‐free bSSFP images from multi‐coil multi‐acquisition datasets. Method: Previous techniques either assume that a naïve coil‐combination is performed a priori resulting in suboptimal artifact suppression, or that artifact suppression is performed for each coil separately at the expense of significant computational burden. Here we propose a tailored method that factorizes the estimation of coil and bSSFP sensitivity profiles for improved accuracy and/or speed. Results: In vivo experiments show that the proposed method outperforms naïve coil‐combination and coil‐by‐coil processing in terms of both reconstruction quality and time. Conclusion: The proposed method enables computationally efficient artifact suppression for phase‐cycled bSSFP imaging with modern coil arrays. Rapid imaging applications can efficiently benefit from the improved robustness of bSSFP imaging against field inhomogeneity.