The use of Proton Resonance Frequency (PRF) based thermometry with thermal therapy procedures is indispensable. Variation in background phase due to motion related changes in B0 is a major source of inaccuracy in PRF thermometry. In this work we propose a novel Principal Component Analysis (PCA) based multi-baseline phase correction approach. We compare this approach with two existing methods using in-vivo human brain and heart data, and demonstrate significant reduction in bias as well as variance of temperature difference estimates. The proposed approach may increase the accuracy of PRF thermometry in or near moving organs, and hence result in improved clinical outcome.
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