- Conference date: 24–26 September 2009
- Location: Aix‐en‐Provence (France)
In this study we present results demonstrating how information from thermal and acoustic modeling can be used to improve the monitoring of MR guided high intensity focused ultrasound (MRgHIFU) treatments. A model predictive filtering (MPF) algorithm has been developed to combine thermal model predictions of how the temperature distribution evolves with undersampled k‐space data to create temperature maps with good spatial resolution, fast scan times and large volume coverage. The tissue thermal and acoustic properties are determined using both MR temperature data, acquired during a pre‐treatment step, and ultrasound beam simulation software. A 4‐point, electronically steered HIFU heating experiment was performed with a 256‐element phased array transducer on an agar phantom to validate the method. At a data reduction factor of 9, the MPF algorithm was able to reconstruct temperature maps that correlated very well with fully sampled PRF temperature maps for heating at on‐axis and off‐axis locations.
- Thermal models
- Acoustic modeling
- Acoustic signal processing
- Acoustical properties
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