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Brain-Shift Compensation by Non-Rigid Registration of Intra-Operative Ultrasound Images With Preoperative Mr Images Based on Residual Complexity Publisher Pubmed



Farnia P1, 2 ; Ahmadian A1, 2 ; Shabanian T3 ; Serej ND1, 2 ; Alirezaie J4
Authors
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Authors Affiliations
  1. 1. Image-Guided Intervention Group, Research Centre of Biomedical Technology and Robotics, RCBTR, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran
  4. 4. Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada

Source: International Journal of Computer Assisted Radiology and Surgery Published:2015


Abstract

Purpose: Compensation for brain shift is often necessary for image-guided neurosurgery, requiring registration of intra-operative ultrasound (US) images with preoperative magnetic resonance images (MRI). A new image similarity measure based on residual complexity (RC) to overcome challenges of registration of intra-operative US and preoperative MR images was developed and tested. Method: A new two-stage method based on the matching echogenic structures such as sulci is achieved by optimizing the residual complexity value in the wavelet domain between the ultrasound image and the probabilistic map of the MR image. The proposed method is a compromise between feature-based and intensity-based approaches. Evaluation was performed using a specially designed brain phantom and an in vivo patient data set. Result: The results of the phantom data set registration confirmed that the proposed objective function outperforms the accuracy of adapted RC for multi-modal cases by 48 %. The mean fiducial registration error reached 1.17 and 2.14 mm when the method was applied on phantom and clinical data sets, respectively. Conclusion: This improved objective function based on RC in the wavelet domain enables accurate non-rigid multi-modal (US and MRI) image registration which is robust to noise. This technology is promising for compensation of intra-operative brain shift in neurosurgery. © 2014, CARS.
1. Curvelet Based Residual Complexity Objective Function for Non-Rigid Registration of Pre-Operative Mri With Intra-Operative Ultrasound Images, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society# EMBS (2016)
2. Co-Sparse Analysis Model Based Image Registration to Compensate Brain Shift by Using Intra-Operative Ultrasound Imaging, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society# EMBS (2018)
6. A Projected Landmark Method for Reduction of Registration Error in Image-Guided Surgery Systems, International Journal of Computer Assisted Radiology and Surgery (2015)
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