Run-time motion and first-order shim control by expanded servo navigation.
Magn Reson Med
; 93(1): 166-182, 2025 Jan.
Article
in En
| MEDLINE
| ID: mdl-39188123
ABSTRACT
PURPOSE:
To provide a navigator-based run-time motion and first-order field correction for three-dimensional human brain imaging with high precision, minimal calibration and acquisition, and fast processing.METHODS:
A complex-valued linear perturbation model with feedback control is extended to estimate and correct for gradient shim fields using orbital navigators (2.3 ms). Two approaches for sensitizing the model to gradient fields are presented, one based on finite differences with three additional navigators, and another projection-based approximation requiring no additional navigators. A mechanism for noise decorrelation of the matrix and the data is proposed and evaluated to reduce unwanted parameter biases.RESULTS:
The rigid motion and first-order field control achieves robust motion and gradient shim corrections improving image quality in a series of phantom and in vivo experiments with varying field conditions. In phantom scans, magnet drifts, forced gradient field perturbations and field distortions from shifts of a second bottle phantom are successfully corrected. Field estimates of the magnet drifts are in good agreement with concurrent field probe measurements. For in vivo scans, the proposed method mitigates field variations from torso motions while being robust to head motion. In vivo gradient field precisions were 30 nT / m $$ 30\;\mathrm{nT}/\mathrm{m} $$ along with single-digit micrometer and millidegree rigid precisions.CONCLUSION:
The navigator-based method achieves accurate, high-precision run-time motion and field corrections with low sequence impact and calibration requirements.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Algorithms
/
Brain
/
Magnetic Resonance Imaging
/
Phantoms, Imaging
/
Imaging, Three-Dimensional
Limits:
Humans
Language:
En
Journal:
Magn Reson Med
Journal subject:
DIAGNOSTICO POR IMAGEM
Year:
2025
Document type:
Article
Affiliation country:
Switzerland
Country of publication:
United States