Improving the referenceless MR thermometry using adaptive ROI

Most referenceless MR thermometry methods use a large and fixed ROI to ensure to contain the whole heated region. However, the heated region is unknown and hard to estimate before heat occurs. The large ROI also compromises the accuracy in some measurements. This work proposes to use adaptive size of ROI for real-time referenceless thermometry. The size of ROI is decided by the size of heated region, which is measured from previous temperature map. The results would increase the accuracy of referenceless methods and improve the automation of referenceless thermometry for real-time monitoring.

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