Browsing by Subject "Steady state free precessions"
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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 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.