Automatic nonrigid calibration of image registration for real time MR-guided HIFU ablations of mobile organs.

IEEE Trans Med Imaging

Laboratory for Molecular and Functional Imaging: From Physiology to Therapy, FRE 3313 CNRS/University of Bordeaux 2, 33076 Bordeaux, France.

Published: October 2011

AI Article Synopsis

  • Real-time MRI is becoming essential for interventional therapies, necessitating precise motion estimation for moving targets, which can be optimized using image registration algorithms.
  • The paper critiques existing anatomical image similarity criteria for assessing motion accuracy, introducing a new criterion based on local magnetic field distribution, which proves more effective.
  • Experimental results show that the proposed criterion led to improved accuracy in motion estimation, reducing displacement errors from an average of 1.5 mm to 1 mm, particularly benefiting kidney and liver procedures.

Article Abstract

Real time magnetic resonance imaging (MRI) is rapidly gaining importance in interventional therapies. An accurate motion estimation is required for mobile targets and can be conveniently addressed using an image registration algorithm. Since the adaptation of the control parameters of the algorithm depends on the application (targeted organ, location of the tumor, slice orientation, etc.), typically an individual calibration is required. However, the assessment of the estimated motion accuracy is difficult since the real target motion is unknown. In this paper, existing criteria based only on anatomical image similarity are demonstrated to be inadequate. A new criterion is introduced, which is based on the local magnetic field distribution. The proposed criterion was used to assess, during a preparative calibration step, the optimal configuration of an image registration algorithm derived from the Horn and Schunck method. The accuracy of the proposed method was evaluated in a moving phantom experiment, which allows the comparison with the known motion pattern and to an established criterion based on anatomical images. The usefulness of the method for the calibration of optical-flow based algorithms was also demonstrated in vivo under conditions similar to thermo-ablation for the abdomen of twelve volunteers. In average over all volunteers, a resulting displacement error of 1.5 mm was obtained (largest observed error equal to 4-5 mm) using a criterion based on anatomical image similarity. A better average accuracy of 1 mm was achieved using the proposed criterion (largest observed error equal to 2 mm). In both kidney and liver, the proposed criterion was shown to provide motion field accuracy in the range of the best achievable.

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http://dx.doi.org/10.1109/TMI.2011.2144615DOI Listing

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