Browsing by Subject "Banding artifact"
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Item Open Access Accelerated phase-cycled SSFP imaging with compressed sensing(Institute of Electrical and Electronics Engineers Inc., 2015) Çukur, T.Balanced steady-state free precession (SSFP) imaging suffers from irrecoverable signal losses, known as banding artifacts, in regions of large B0 field inhomogeneity. A common solution is to acquire multiple phase-cycled images each with a different frequency sensitivity, such that the location of banding artifacts are shifted in space. These images are then combined to alleviate signal loss across the entire field-of-view. Although high levels of artifact suppression are viable using a large number of images, this is a time costly process that limits clinical utility. Here, we propose to accelerate individual acquisitions such that the overall scan time is equal to that of a single SSFP acquisition. Aliasing artifacts and noise are minimized by using a variable-density random sampling pattern in k-space, and by generating disjoint sampling patterns for separate acquisitions. A sparsity-enforcing method is then used for image reconstruction. Demonstrations on realistic brain phantom images, and in vivo brain and knee images are provided. In all cases, the proposed technique enables robust SSFP imaging in the presence of field inhomogeneities without prolonging scan times. © 2014 IEEE.Item Open Access bSSFP phase correction and its use in magnetic resonance electrical properties tomography(International Society for Magnetic Resonance in Medicine, 2019) Özdemir, Safa; İder, Yusuf ZiyaPurpose Balanced steady‐state free precession (bSSFP) sequence is widely used because of its high SNR and high speed. However, bSSFP images suffer from “banding artifact” caused by B0 inhomogeneity. In this article, we propose a method to remove this artifact in bSSFP phase images and investigate the usage of the corrected phase images in phase‐based magnetic resonance electrical properties tomography (MREPT). Theory and Methods Two bSSFP phase images, obtained with different excitation frequencies, are collaged to get rid of the regions containing banding artifacts. Phase of the collaged bSSFP image is the sum of the transceive phase of the RF system and an error term that depends on B0 and T2. By using B0 and T2 maps, this error is eliminated from bSSFP phase images by using pixel‐wise corrections. Conductivity maps are obtained from the uncorrected and the corrected phase images using the phase‐based cr‐MREPT method. Results Phantom and human experiment results of the proposed method are illustrated for both phase images and conductivity maps. It is shown that uncorrected phase images yield unacceptable conductivity images. When only B0 information is used for phase correction conductivity, reconstructions are substantially improved, and yet T2 information is still needed to fully recover accurate and undistorted conductivity images. Conclusions With the proposed technique, B0 sensitivity of the bSSFP phase images can be removed by using B0 and T2 maps. It is also shown that corrected bSSFP phase images are of sufficient quality to be used in conductivity imaging.Item 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, TolgaObjective: 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.Item Open Access Huber function based reconstruction in accelerated phase-cycled bSSFP acquisitions for increased detection performance(IEEE, 2017) Ilıcak, Efe; Çukur, TolgaBalanced steady-state free precession imaging suffers from irrecoverable signal losses, called banding artifacts. A common way to alleviate banding artifacts without sacrificing scan-efficiency is to use multiple-acquisition methods that combine phase-cycled images. However, soft thresholding applications used during the recovery can reduce the detection performance and image quality. In this study, a reconstruction strategy that applies Huber function to increase detection sensitivity on small coefficients is evaluated. This strategy is compared with conventional methods in terms of peak signal to noise ratio and structural similarity index.Item Open Access Profile-encoding reconstruction for multiple-acquisition balanced steady-state free precession imaging(John Wiley and Sons Inc., 2017) Ilicak, Efe; Senel, Lutfi Kerem; Biyik, Erdem; Çukur, TolgaPurpose: The scan-efficiency in multiple-acquisition balanced steady-state free precession imaging can be maintained by accelerating and reconstructing each phase-cycled acquisition individually, but this strategy ignores correlated structural information among acquisitions. Here, an improved acceleration framework is proposed that jointly processes undersampled data across N phase cycles. Methods: Phase-cycled imaging is cast as a profile-encoding problem, modeling each image as an artifact-free image multiplied with a distinct balanced steady-state free precession profile. A profile-encoding reconstruction (PE-SSFP) is employed to recover missing data by enforcing joint sparsity and total-variation penalties across phase cycles. PE-SSFP is compared with individual compressed-sensing and parallel-imaging (ESPIRiT) reconstructions. Results: In the brain and the knee, PE-SSFP yields improved image quality compared to individual compressed-sensing and other tested methods particularly for higher N values. On average, PE-SSFP improves peak SNR by 3.8 ± 3.0 dB (mean ± s.e. across N = 2–8) and structural similarity by 1.4 ± 1.2% over individual compressed-sensing, and peak SNR by 5.6 ± 0.7 dB and structural similarity by 7.1 ± 0.5% over ESPIRiT. Conclusion: PE-SSFP attains improved image quality and preservation of high-spatial-frequency information at high acceleration factors, compared to conventional reconstructions. PE-SSFP is a promising technique for scan-efficient balanced steady-state free precession imaging with improved reliability against field inhomogeneity. Magn Reson Med 78:1316–1329, 2017.