Calibrationless Reconstruction Methods in Magnetic Resonance ImagingMS25

Magnetic Resonance Imaging (MRI) is a powerful tomographic imaging technique based on sampling of Fourier data in a series of measurements. To reduce the number of measurements, parallel imaging utilizes data from multiple receive coils which each produces a signal modulated by a different spatial sensitivity profile. We will discuss robust algorithms for parallel imaging that avoid explicit calibration of the sensitivities by formulating reconstruction as a non-linear inverse problem.

This presentation is part of Minisymposium “MS25 - Bilinear and quadratric problems in imaging
organized by: Felix Krahmer (Technical University of Munich, Department of Mathematics) , Kristian Bredies (Universität Graz) .

Martin Uecker (University Medical Center Göttingen)
Sebastian Rosenzweig (University Medical Center Göttingen)
H. Christian M. Holme (University Medical Center Göttingen)
blind deconvolution, computational imaging, image reconstruction, inverse problems, magnetic resonance imaging, nonlinear optimization