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Patch-based field-of-view matching in multi-modal images for electroporation-based ablations.

L Lafitte1, R Giraud2, C Zachiu3

  • 1University of Bordeaux, IMB, UMR CNRS 5251, INRIA Project team Monc, F-33405 Talence Cedex, France.

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society
|July 6, 2020
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Summary

This study introduces a fast patch-based method to align different medical imaging fields-of-view (FOV) for improved deformable image registration (DIR). The approach enhances accuracy in multi-modal imaging, crucial for interventional procedures.

Keywords:
Interventional proceduresMulti-modal image registrationPatch-based matching

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Area of Science:

  • Medical Imaging
  • Image Registration
  • Interventional Radiology

Background:

  • Multi-modal imaging (CBCT, CT, MR) provides complementary data in interventional workflows.
  • Accurate spatial alignment of diverse imaging modalities is essential for merging functional and structural information.
  • Existing deformable image registration (DIR) methods struggle with differing fields-of-view (FOV) across modalities.

Purpose of the Study:

  • To develop a fast, patch-based method for aligning fields-of-view (FOV) in multi-modal 3D medical images.
  • To improve deformable image registration (DIR) accuracy, especially when imaging modalities have significantly different FOVs.
  • To assess the method's suitability for real-time, on-line interventional procedures.

Main Methods:

  • A novel patch-based approach combined with a state-of-the-art multi-modal image similarity metric.
  • Calculating patch shifts to determine the most frequent shift value for FOV adjustment.
  • Evaluating performance on 30 pairs of pre-/per-operative irreversible electroporation (IRE) images (CT to CBCT, MRI to CBCT).

Main Results:

  • The patch-based regional registration approach offers a balance between voxel-wise and global shift methods.
  • The method demonstrated benefits for CT to CBCT and MRI to CBCT registration, particularly with disparate FOVs.
  • Computational requirements are compatible with clinical on-line procedures using commodity hardware.

Conclusions:

  • The proposed patch-based FOV alignment method effectively addresses challenges in multi-modal DIR with differing image FOVs.
  • This technique is beneficial for improving image registration accuracy in interventional procedures like irreversible electroporation.
  • The method's speed and efficiency make it a valuable tool for real-time image guidance in interventions.