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Abstract #1558

Kalman Filtering for Undersampeled Continuous Volumetric MR-Temperature Imaging

Baudouin Denis de Senneville1, 2, Sbastien Roujol, 23, Silke Hey2, 4, Chrit Moonen1, 2, Mario Ries1, 2

1Imaging Division, UMC Utrecht, Utrecht, Netherlands; 2CNRS / University of Bordeaux 2, IMF, Bordeaux, France; 3Cardiovascular Division, Beth Israel Deaconess, Medical Center, Harvard Medical School, Boston, United States; 4Philips Healthcare, Best, Netherlands

Volumetric real time MR-thermometry on moving organs for therapy guidance is challenging. As a result, recent efforts focused on the possibility to exploit the physical knowledge of the heating process for the artefact free reconstruction of 3D MR-temperature maps from under-sampled MR-data. This study investigates the possibility to reconstruct continuous volumetric temperature data from spatio-temporally under-sampled 3D MR-temperature maps using an Extended Kalman Filter with the bio-heat transfer equation as the model predictor. The proposed method was characterized with in-vivo HIFU experiments on porcine kidney.