PCA-Based Magnetic Field Modeling : Application for On-Line MR Temperature Monitoring

• DOI: 10.1007/978-3-540-75759-7_50
• Publication Date: 2007-10-11T18:22:34Z
• Authors: G. Maclair; B. Denis de Senne...; M. Ries; B. Quesson; P. Desbarats; J. Benois-Pineau; C. T. W. Moonen
• Keywords: Principal Component Analysis; Reproducibility of Results; Magnetic Resonance Imaging; Sensitivity and Specificity; Body Temperature; 03 medical and health sciences; 0302 clinical medicine; [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]; Thermography; [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]; Data Interpretation, Statistical; Abdomen; Image Interpretation, Computer-Assisted; Humans; Algorithms

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.