Abstract #4060
Improving the referenceless MR thermometry using adaptive ROI
Changjun Tie 1 , Chao Zou 1 , and Xin Liu 1
1
Shenzhen Institutes of Advanced Technology,
Chinese Academy of Sciences, Shenzhen, Guangdong, China
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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