PCA-based magnetic field modeling: application for on-line MR temperature monitoring

Authors:
G. Maclair;B. Denis De Senneville;M. Ries;B. Quesson;P. Desbarats;J. Benois-Pineau;C. T. W. Moonen
Affiliations:
IMF, UMR, CNRS, Université Bordeaux 2, Bordeaux and CNRS, Université Bordeaux 1, Talence;IMF, UMR, CNRS, Université Bordeaux 2, Bordeaux;IMF, UMR, CNRS, Université Bordeaux 2, Bordeaux;IMF, UMR, CNRS, Université Bordeaux 2, Bordeaux;CNRS, Université Bordeaux 1, Talence;CNRS, Université Bordeaux 1, Talence;IMF, UMR, CNRS, Université Bordeaux 2, Bordeaux
Venue:
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Year:
2007

Citing 2
Cited 0

Adapting optical-flow to measure object motion in reflectance and X-ray image sequences

Proc. of the ACM SIGGRAPH/SIGART interdisciplinary workshop on Motion: representation and perception
Learning Parameterized Models of Image Motion

CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)

Quantified Score

Hi-index	0.00

Visualization

Abstract

Magnetic Resonance (MR) temperature mapping can be used to monitor temperature changes during minimally invasive thermal therapies. However, MR-thermometry contains artefacts caused by phase errors induced by organ motion in inhomogeneous magnetic fields. This paper proposes a novel correction strategy based on a Principal Component Analysis (PCA) to estimate magnetic field perturbation assuming a linear magnetic field variation with organ displacement. The correction method described in this paper consists of two steps: a magnetic field perturbation model is computed in a learning step; subsequently, during the intervention, this model is used to reconstruct the magnetic field perturbation corresponding to the actual organ position which in turns allow computation of motion corrected thermal maps.