Siemens Aktiengesellschaft

Siemens Healthcare Gmbh

Sajan Goud Lingala

Mariappan S Nadar

Boris Mailhe

Marcel Dominik Nickel

Li Zhang

Christophe Chefd'hotel

Robert Grimm

Nirmal Janardhanan

Jyotipriya Das

Mathews Jacob

For radial sampling in magnetic resonance imaging (MRI), a rescaling factor is determined from k-space data for each coil. The rescale factor is inversely proportional to the streak energy in the k-space data. The k-space data from the coils is rescaled for reconstruction, such as weighting the k-space data by the rescale factor in a data consistency term of iterative reconstruction. The rescale factor is additionally or alternatively used to determine a correction field for correction of intensity bias applied to intensities in the image-object space after reconstruction. These approaches may result in a diagnostically useful bias-corrected image with reduced streak artifact while benefiting from the efficient computation (i.e., computer operates to reconstruct more quickly).

Streak artifact reduction in magnetic resonance imaging

Methods and a system to unify reconstruction and motion estimation steps in first pass cardiac perfusion MRI include a global objective function that meets data consistency, spatial smoothness, motion and contrast dynamics constraints. The global objective decomposed into simpler sub-problems which include low pass filtering of a deformed object, TV shrinkage, analytical Fourier replacement and an lminimizing problem. A registration tool based on the local cross-correlation similarity measure and enabled to perform both rigid and flexile deformations, is applied. Registration parameters are tuned by rigid, semi rigid and flexible models at different stages of iterations. A system to perform the methods is also disclosed.

Unifying reconstruction and motion estimation in first pass cardiac perfusion imaging

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Rochester, NY, United States of America

Sajan Goud Lingala