MS Thesis Presentation: “Efficient Parameter Mapping for Magnetic Resonance Imaging,” Kübra Keskin (EE), UMRAM, 10AM July 25 (EN)

SEMINAR: “Efficient Parameter Mapping for Magnetic Resonance Imaging”
Kübra Keskin

M.S. in Electrical and Electronics Engineering
Assoc. Prof. Dr. Tolga Çukur

The seminar will be on Thursday, July 25, 2019 at 10:00 @UMRAM

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 field inhomogeneity, which leads to banding artifacts near regions of relatively large off-resonance shifts. To suppress these artifacts, 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 has long been employed to eliminate banding artifacts due to field 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 effective, they often need a large number of acquisitions, inherently limiting scan efficiency. In this thesis, we propose a new method for parameter mapping with improved efficiency and accuracy in phase-cycled 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 identification to improve estimation accuracy. Simulated, phantom and in vivo experiments demonstrate that the proposed method enables improved parameter mapping with fewer acquisitions.