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On removing interpolation and resampling artifacts in rigid image registration.

Iman Aganj1, Boon Thye Thomas Yeo, Mert R Sabuncu

  • 1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA. iman@nmr.mgh.harvard.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|October 19, 2012
PubMed
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Resampling artifacts in image registration can cause inaccuracies. This study introduces an integral cost function and oscillatory interpolation kernels to improve registration accuracy, overcoming aliasing issues.

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Area of Science:

  • Medical Imaging
  • Computer Vision
  • Image Processing

Background:

  • Conventional image registration methods using interpolation and summation approximations are prone to resampling artifacts.
  • These artifacts degrade registration accuracy by introducing local optima, altering gradients, and causing asymmetry.

Purpose of the Study:

  • To analytically demonstrate the causes of resampling artifacts in image registration.
  • To propose an integral formulation of the sum-of-squared-differences cost function for improved accuracy.
  • To introduce oscillatory isotropic interpolation kernels to mitigate aliasing during rotation.

Main Methods:

  • Analytical comparison of resampling inclusion and avoidance.
  • Formulation of a sum-of-squared-differences cost function as a continuous integral.
  • Development and application of oscillatory isotropic interpolation kernels.
  • Experimental validation on brain, fingerprint, and white noise images.

Main Results:

  • The integral cost function shows higher accuracy than the traditional sum form in basic image registration.
  • Oscillatory isotropic interpolation kernels effectively overcome aliasing issues caused by varying sampling rates during rotation.
  • Experiments confirm the superior performance of the integral registration cost function and the radial interpolation kernel.

Conclusions:

  • Image registration accuracy is significantly impacted by resampling artifacts inherent in conventional methods.
  • An integral cost function and novel interpolation kernels offer a more robust and accurate approach to image registration.
  • The proposed methods demonstrate improved performance across various image types and coordinate systems.