A multicontrast imaging method using steady‐state free precession with alternating <scp>RF</scp> flip angles

Kim, Joon-Soo; Seo, Hyunseok; So, Seohee; Park, HyunWook

doi:10.1002/mrm.27342

Cited by 2 publications

(2 citation statements)

References 23 publications

(40 reference statements)

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“…That said, bSSFP might yield suboptimal contrast for other applications that focus on primarily T 2 -or T 1 -driven differences among soft tissues. A powerful approach to address this limitation is to estimate relaxation parameters from bSSFP acquisitions, and to either directly examine the estimates [22] or synthesize images of desired contrasts [23]. Many previous methods in this domain rely on introduction of additional T 1 -or T 2 -weighting information into measurements.…”

Section: Introductionmentioning

confidence: 99%

Constrained Ellipse Fitting for Efficient Parameter Mapping With Phase-Cycled bSSFP MRI

Keskin

Yılmaz²,

Çukur³

2022

IEEE Trans. Med. Imaging

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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 T 2 /T 1 -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 phasecycled 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 dictionarybased identification to improve estimation accuracy. CELF generates maps of T 1 , T 2 , off-resonance and on-resonant bSSFP signal by employing a separate B 1 map to mitigate sensitivity to flip angle variations. Our results indicate that CELF can produce accurate off-resonance and bandingfree 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.

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Section: Introductionmentioning

confidence: 99%

Constrained Ellipse Fitting for Efficient Parameter Mapping With Phase-Cycled bSSFP MRI

Keskin

Yılmaz²,

Çukur³

2022

IEEE Trans. Med. Imaging

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“…MRI usually takes tens of minutes to more than an hour to cover whole imaging volume. Thus, partial acquisition of the k-space is applied to reduce the scan time [1]. Under Nyquist sampling rate in the Cartesian coordinates, however, the problems of ghost (aliasing) artifacts in the image should be solved.…”

Section: Introductionmentioning

confidence: 99%

A Dual Domain Network For MRI Reconstruction Using Gabor Loss

Seo¹,

Shin²,

Kyung

2021

2021 IEEE International Conference on Image Processing (ICIP)

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Fast magnetic resonance imaging (MRI) scan is usually achieved by undersampling in k-space, and reconstruction methods for image domain is indispensable. Conventional reconstruction methods rely on independent sensitivity maps of the receiver coils to synthesize the components of the spatial harmonics in k-space. In recent years, deep learningbased MRI algorithms have been providing more accurate reconstructed image than the traditional results. Nonetheless, there is room for improvement. In this study, we proposed a new deep learning-based reconstruction algorithm to use image and k-space domain data simultaneously. The Gabor filter was also defined to effectively incorporate two different domain data in learning stage. Experimental results using real MRI data showed that the proposed method outperforms other deep learning-based algorithms for three metrics of nMSE, SSIM, and VIF.

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A multicontrast imaging method using steady‐state free precession with alternating RF flip angles

Abstract: The proposed method can be a useful tool for clinical diagnosis, such as the cartilage segmentation and the fast screening of lesions.

Cited by 2 publications

References 23 publications

Constrained Ellipse Fitting for Efficient Parameter Mapping With Phase-Cycled bSSFP MRI

Constrained Ellipse Fitting for Efficient Parameter Mapping With Phase-Cycled bSSFP MRI

A Dual Domain Network For MRI Reconstruction Using Gabor Loss

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