| PHYSICS AND ENGINEERING MECHANICS |
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Kalman filtering and bio-heat transfer model based real-time MR temperature imaging for increased accuracy |
| WU Jinchao1, QIU Shihan2, LI Muheng1, WEI Xing3, CHEN Bingyao3, YING Kui1 |
1. Key Laboratory of Particle and Radiation Imaging of Ministry of Education, Department of Engineering Physics, Tsinghua University, Beijing 100084, China;
2. Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China;
3. Department of Orthopedics, Aero Space Center Hospital, Beijing 100048, China |
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Abstract Magnetic resonance temperature imaging is an important technique to ensure safe and effective use of tumor hyperthermia ablation by providing real-time, global temperature field monitoring. In clinical trials, however, the signal-to-noise ratio (SNR) of magnetic resonance temperature imaging is relatively low, with the signal quality degrading more with fast imaging sequences. To solve this problem, a bio-heat transfer based Kalman filtering model is developed for magnetic resonance temperature imaging where the bio-heat transfer equation is transformed into the form of a Kalman state transition matrix. Then the simulated temperature is combined with the measured temperature to create an accurate, high SNR estimated temperature. Clinical simulations show that this method reduces the temperature measurement root mean square error from 6℃ to 2℃ and the physical phantom experiment shows that this method reduces the root mean square error of the measured temperature and the true temperature from 1.927℃ to 0.735℃ while significantly improving the SNR.
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| Keywords
magnetic resonance imaging
magnetic resonance temperature imaging
bio-heat transfer model
Kalman filter
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Issue Date: 03 April 2020
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2020,
Vol. 60
