In order to reduce geometric distortion phenomena in MR images, every MRI system main magnet undergoes a shimming process. Since this process aims at optimizing magnetic field homogeneity within a so-called uniformity sphere, image quality outside this sphere is neglected. Since the fields vary smoothly in space, MR signal-to-noise ratio is still non-zero just outside the uniformity region, but correction of MR image distortion fails due to lack of magnetic field knowledge outside it. We propose a novel algorithm for measuring all the fields involved in the generation of images. Our proposal is based on exploitation of the distortion which can be observed in images of a known phantom. The proposed method will enable measurement of the fields in a region that can be bigger than the uniformity sphere depending on the phantom dimensions.

Acquaviva, R., Mangione, S., & Garbo, G. (2018). Image-based MRI Gradient Estimation. MAGNETIC RESONANCE IMAGING, 49, 138-144 [10.1016/j.mri.2017.12.028].

Image-based MRI Gradient Estimation

R. Acquaviva;S. Mangione
;
G. Garbo
2018

Abstract

In order to reduce geometric distortion phenomena in MR images, every MRI system main magnet undergoes a shimming process. Since this process aims at optimizing magnetic field homogeneity within a so-called uniformity sphere, image quality outside this sphere is neglected. Since the fields vary smoothly in space, MR signal-to-noise ratio is still non-zero just outside the uniformity region, but correction of MR image distortion fails due to lack of magnetic field knowledge outside it. We propose a novel algorithm for measuring all the fields involved in the generation of images. Our proposal is based on exploitation of the distortion which can be observed in images of a known phantom. The proposed method will enable measurement of the fields in a region that can be bigger than the uniformity sphere depending on the phantom dimensions.
Settore ING-INF/03 - Telecomunicazioni
Acquaviva, R., Mangione, S., & Garbo, G. (2018). Image-based MRI Gradient Estimation. MAGNETIC RESONANCE IMAGING, 49, 138-144 [10.1016/j.mri.2017.12.028].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10447/254010
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